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Image Processing Using FPGAs

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ISBN: 9783038979180 9783038979197 Year: Pages: 204 DOI: 10.3390/books978-3-03897-919-7 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Computer Science
Added to DOAB on : 2019-06-26 08:44:06
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This book presents a selection of papers representing current research on using field programmable gate arrays (FPGAs) for realising image processing algorithms. These papers are reprints of papers selected for a Special Issue of the Journal of Imaging on image processing using FPGAs. A diverse range of topics is covered, including parallel soft processors, memory management, image filters, segmentation, clustering, image analysis, and image compression. Applications include traffic sign recognition for autonomous driving, cell detection for histopathology, and video compression. Collectively, they represent the current state-of-the-art on image processing using FPGAs.

Entropy in Image Analysis

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ISBN: 9783039210923 9783039210930 Year: Pages: 456 DOI: 10.3390/books978-3-03921-093-0 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2019-06-26 08:44:06
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Image analysis is a fundamental task for extracting information from images acquired across a range of different devices. Since reliable quantitative results are requested, image analysis requires highly sophisticated numerical and analytical methods—particularly for applications in medicine, security, and remote sensing, where the results of the processing may consist of vitally important data. The contributions to this book provide a good overview of the most important demands and solutions concerning this research area. In particular, the reader will find image analysis applied for feature extraction, encryption and decryption of data, color segmentation, and in the support new technologies. In all the contributions, entropy plays a pivotal role.

Keywords

image retrieval --- multi-feature fusion --- entropy --- relevance feedback --- chaotic system --- image encryption --- permutation-diffusion --- SHA-256 hash value --- dynamic index --- entropy --- keyframes --- Shannon’s entropy --- sign languages --- video summarization --- video skimming --- image encryption --- multiple-image encryption --- two-dimensional chaotic economic map --- security analysis --- image encryption --- chaotic cryptography --- cryptanalysis --- chosen-plaintext attack --- image information entropy --- blind image quality assessment (BIQA) --- information entropy, natural scene statistics (NSS) --- Weibull statistics --- discrete cosine transform (DCT) --- ultrasound --- hepatic steatosis --- Shannon entropy --- fatty liver --- metabolic syndrome --- multi-exposure image fusion --- texture information entropy --- adaptive selection --- patch structure decomposition --- image encryption --- time-delay --- random insertion --- information entropy --- chaotic map --- uncertainty assessment --- deep neural network --- random forest --- Shannon entropy --- positron emission tomography --- reconstruction --- field of experts --- additive manufacturing --- 3D prints --- 3D scanning --- image entropy --- depth maps --- surface quality assessment --- machine vision --- image analysis --- Arimoto entropy --- free-form deformations --- normalized divergence measure --- gradient distributions --- nonextensive entropy --- non-rigid registration --- pavement --- macrotexture --- 3-D digital imaging --- entropy --- decay trend --- discrete entropy --- infrared images --- low contrast --- multiscale top-hat transform --- image encryption --- DNA encoding --- chaotic cryptography --- cryptanalysis --- image privacy --- computer aided diagnostics --- colonoscopy --- Rényi entropies --- structural entropy --- spatial filling factor --- binary image --- Cantor set --- Hénon map --- Minkowski island --- prime-indexed primes --- Ramanujan primes --- Kapur’s entropy --- color image segmentation --- whale optimization algorithm --- differential evolution --- hybrid algorithm --- Otsu method --- image encryption --- dynamic filtering --- DNA computing --- 3D Latin cube --- permutation --- diffusion --- fuzzy entropy --- electromagnetic field optimization --- chaotic strategy --- color image segmentation --- multilevel thresholding --- contrast enhancement --- sigmoid --- Tsallis statistics --- q-exponential --- q-sigmoid --- q-Gaussian --- ultra-sound images --- person re-identification --- image analysis --- hash layer --- quantization loss --- Hamming distance --- cross-entropy loss --- image entropy --- Shannon entropy --- generalized entropies --- image processing --- image segmentation --- medical imaging --- remote sensing --- security

Intelligent Imaging and Analysis

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ISBN: 9783039219209 9783039219216 Year: Pages: 492 DOI: 10.3390/books978-3-03921-921-6 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2020-04-07 23:07:08
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Imaging and analysis are widely involved in various research fields, including biomedical applications, medical imaging and diagnosis, computer vision, autonomous driving, and robot controls. Imaging and analysis are now facing big changes regarding intelligence, due to the breakthroughs of artificial intelligence techniques, including deep learning. Many difficulties in image generation, reconstruction, de-noising skills, artifact removal, segmentation, detection, and control tasks are being overcome with the help of advanced artificial intelligence approaches. This Special Issue focuses on the latest developments of learning-based intelligent imaging techniques and subsequent analyses, which include photographic imaging, medical imaging, detection, segmentation, medical diagnosis, computer vision, and vision-based robot control. These latest technological developments will be shared through this Special Issue for the various researchers who are involved with imaging itself, or are using image data and analysis for their own specific purposes.

Keywords

image inspection --- non-referential method --- feature extraction --- fault pattern learning --- weighted kernel density estimation (WKDE) --- rail surface defect --- UAV image --- defect detection --- gray stretch maximum entropy --- image enhancement --- defect segmentation --- semi-automatic segmentation --- MR spine image --- vertebral body --- graph-based segmentation --- correlation --- surface defect of steel sheet --- image segmentation --- saliency detection --- low-rank and sparse decomposition --- intervertebral disc --- segmentation --- convolutional neural network --- fine grain segmentation --- U-net --- deep learning --- magnetic resonance image --- lumbar spine --- image adjustment --- colorfulness --- contrast --- sharpness --- high dynamic range --- local registration --- iterative closest points --- multimodal medical image registration --- machine vision --- point cloud registration --- greedy projection triangulation --- local correlation --- three-dimensional imaging --- optimization arrangement --- cavitation bubble --- water hydraulic valve --- defect inspection --- image processing --- feature extraction --- classification methods --- medical image registration --- image alignment in medical images --- misalignment correction in MRI --- midsagittal plane extraction --- symmetry detection --- PCA --- conformal mapping --- mesh parameterization --- mesh partitioning --- pixel extraction --- texture mapping --- image analysis --- image retrieval --- spatial information --- image classification --- computer vision --- image restoration --- motion deburring --- image denoising --- sparse feedback --- Image processing --- segmentation --- spline --- grey level co-occurrence matrix --- gradient detection --- threshold selection --- OpenCV --- machine learning --- transfer learning --- Inception-v3 --- geological structure images --- convolutional neural networks --- image segmentation --- active contour model --- level set --- signed pressure force function --- image segmentation --- deep learning --- synthetic aperture radar (SAR) --- oil slicks --- segnet --- pectus excavatum --- nuss procedure --- patient-specific nuss bar --- minimally invasive surgery --- computerized numerical control bending machine --- computer-aided design --- computer-aided manufacturing --- statistical body shape model --- self-intersection penalty term --- 3D pose estimation --- 3D semantic mapping --- incrementally probabilistic fusion --- CRF regularization --- road scenes --- deep learning --- medical image classification --- additional learning --- CT image --- automatic training --- GoogLeNet --- intelligent evaluation --- automated cover tests --- deviation of strabismus --- pupil localization --- shape from focus --- wear measurement --- sprocket teeth --- normal distribution operator image filtering --- adaptive evaluation window --- reverse engineering --- human parsing --- depth-estimation --- computational efficiency --- capacity optimization --- underwater visual localization method --- line segment features --- PL-SLAM --- face sketch synthesis --- face sketch recognition --- joint training model --- data imbalance --- Contrast Tomography (CT) --- pre-training strategy --- segmentation --- super-resolution --- dual-channel --- residual block --- convolutional kernel parameter --- long-term and short-term memory blocks --- n/a

Marine Geomorphometry

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ISBN: 9783038979548 9783038979555 Year: Pages: 400 DOI: 10.3390/books978-3-03897-955-5 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2019-06-26 08:44:07
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Geomorphometry is the science of quantitative terrain characterization and analysis, and has traditionally focused on the investigation of terrestrial and planetary landscapes. However, applications of marine geomorphometry have now moved beyond the simple adoption of techniques developed for terrestrial studies, driven by the rise in the acquisition of high-resolution seafloor data and by the availability of user-friendly spatial analytical tools. Considering that the seafloor represents 71% of the surface of our planet, this is an important step towards understanding the Earth in its entirety.This volume is the first one dedicated to marine applications of geomorphometry. It showcases studies addressing the five steps of geomorphometry: sampling a surface (e.g., the seafloor), generating a Digital Terrain Model (DTM) from samples, preprocessing the DTM for subsequent analyses (e.g., correcting for errors and artifacts), deriving terrain attributes and/or extracting terrain features from the DTM, and using and explaining those terrain attributes and features in a given context. Throughout these studies, authors address a range of challenges and issues associated with applying geomorphometric techniques to the complex marine environment, including issues related to spatial scale, data quality, and linking seafloor topography with physical, geological, biological, and ecological processes. As marine geomorphometry becomes increasingly recognized as a sub-discipline of geomorphometry, this volume brings together a collection of research articles that reflect the types of studies that are helping to chart the course for the future of marine geomorphometry.

Keywords

bedforms --- forage fish --- Pacific sand lance --- sediment habitats --- bathymetry --- currents --- seabed mapping --- marine geology --- submarine topography --- marine geomorphology --- terrain analysis --- multibeam echosounder --- bathymetry --- DEM --- satellite imagery --- multi beam echosounder --- filter --- geomorphology --- coral reefs --- Acoustic applications --- object segmentation --- seafloor --- underwater acoustics --- Cretaceous --- Cenomanian–Turonian --- paleobathymetry --- paleoclimate --- paleoceanography --- reconstruction --- simulation --- shelf-slope-rise --- geomorphometry --- GIS --- spatial scale --- spatial analysis --- terrain analysis --- seafloor geomorphometry --- domes --- volcanoes --- digital elevation models (DEMs) --- Canary Basin --- Atlantic Ocean --- cold-water coral --- carbonate mound --- habitat mapping --- spatial prediction --- image segmentation --- geographic object-based image analysis --- random forest --- accuracy --- confidence --- global bathymetry --- Seabed 2030 --- Nippon Foundation/GEBCO --- seafloor mapping technologies --- seafloor mapping standards and protocols --- benthic habitats --- shelf morphology --- eastern Brazilian shelf --- geomorphometry --- terrain analysis --- bathymetry --- surface roughness --- benthic habitat mapping --- python --- geomorphology --- submerged glacial bedforms --- deglaciation --- sedimentation --- multibeam --- acoustic-seismic profiling --- swath geometry --- multibeam spatial resolution --- integration artefacts --- Multibeam bathymetry --- benthic habitat mapping --- multiscale --- Random Forests --- pockmarks --- automated-mapping --- ArcGIS --- Glaciated Margin --- North Sea --- Malin Basin --- Barents Sea --- bathymetry --- thalwegs --- canyons --- Alaska --- Bering Sea --- multibeam sonar --- carbonate banks --- semi-automated mapping --- polychaete --- Northwestern Australia --- Oceanic Shoals Australian Marine Park --- Bonaparte Basin --- Timor Sea --- bathymetry --- digital terrain analysis --- geomorphometry --- geomorphology --- habitat mapping --- marine remote sensing

Machine Learning Techniques Applied to Geoscience Information System and Remote Sensing

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ISBN: 9783039212156 9783039212163 Year: Pages: 438 DOI: 10.3390/books978-3-03921-216-3 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering --- Mechanical Engineering
Added to DOAB on : 2019-12-09 11:49:15
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As computer and space technologies have been developed, geoscience information systems (GIS) and remote sensing (RS) technologies, which deal with the geospatial information, have been rapidly maturing. Moreover, over the last few decades, machine learning techniques including artificial neural network (ANN), deep learning, decision tree, and support vector machine (SVM) have been successfully applied to geospatial science and engineering research fields. The machine learning techniques have been widely applied to GIS and RS research fields and have recently produced valuable results in the areas of geoscience, environment, natural hazards, and natural resources. This book is a collection representing novel contributions detailing machine learning techniques as applied to geoscience information systems and remote sensing.

Keywords

landslide --- bagging ensemble --- Logistic Model Trees --- GIS --- Vietnam --- colorization --- random forest regression --- grayscale aerial image --- change detection --- gully erosion --- environmental variables --- data mining techniques --- SCAI --- GIS --- mapping --- single-class data descriptors --- materia medica resource --- Panax notoginseng --- one-class classifiers --- geoherb --- change detection --- convolutional network --- deep learning --- panchromatic --- remote sensing --- remote sensing image segmentation --- convolutional neural networks --- Gaofen-2 --- hybrid structure convolutional neural networks --- winter wheat spatial distribution --- classification-based learning --- real-time precise point positioning --- convergence time --- ionospheric delay constraints --- precise weighting --- landslide --- weights of evidence --- logistic regression --- random forest --- hybrid model --- traffic CO --- traffic CO prediction --- neural networks --- GIS --- land use/land cover (LULC) --- unmanned aerial vehicle --- texture --- gray-level co-occurrence matrix --- machine learning --- crop --- landslide susceptibility --- random forest --- boosted regression tree --- information gain --- landslide susceptibility map --- ALS point cloud --- multi-scale --- classification --- large scene --- coarse particle --- particulate matter 10 (PM10) --- landsat image --- machine learning --- support vector machine --- high-resolution --- optical remote sensing --- object detection --- deep learning --- transfer learning --- land subsidence --- Bayes net --- naïve Bayes --- logistic --- multilayer perceptron --- logit boost --- change detection --- convolutional network --- deep learning --- panchromatic --- remote sensing --- leaf area index (LAI) --- machine learning --- Sentinel-2 --- sensitivity analysis --- training sample size --- spectral bands --- spatial sparse recovery --- constrained spatial smoothing --- spatial spline regression --- alternating direction method of multipliers --- landslide prediction --- machine learning --- neural networks --- model switching --- spatial predictive models --- predictive accuracy --- model assessment --- variable selection --- feature selection --- model validation --- spatial predictions --- reproducible research --- Qaidam Basin --- remote sensing --- TRMM --- artificial neural network --- n/a

Micro/Nano Manufacturing

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ISBN: 9783039211692 9783039211708 Year: Pages: 208 DOI: 10.3390/books978-3-03921-170-8 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General)
Added to DOAB on : 2019-12-09 11:49:15
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Micro manufacturing involves dealing with the fabrication of structures in the size range of 0.1 to 1000 µm. The scope of nano manufacturing extends the size range of manufactured features to even smaller length scales—below 100 nm. A strict borderline between micro and nano manufacturing can hardly be drawn, such that both domains are treated as complementary and mutually beneficial within a closely interconnected scientific community. Both micro and nano manufacturing can be considered as important enablers for high-end products. This Special Issue of Applied Sciences is dedicated to recent advances in research and development within the field of micro and nano manufacturing. The included papers report recent findings and advances in manufacturing technologies for producing products with micro and nano scale features and structures as well as applications underpinned by the advances in these technologies.

Keywords

fluid jet polishing --- deterministic polishing --- variable pitch path --- residual error optimization --- path adaptability --- chatter identification --- three-dimensional elliptical vibration cutting --- empirical mode decomposition --- intrinsic mode function --- feature extraction --- micro-EDM molds --- micro-lens array --- contactless embossing --- friction coefficient --- micro 3D printing --- micro stereolithography --- process parameter optimization --- Taguchi’s method --- multi-objective particle swarm optimization --- flow control --- culture dish adapter --- small recess structure --- closed environment --- perfusion culture --- optical encoder --- grating --- blaze --- injection molding --- micro assembly --- active alignment --- opto-ASIC --- wafer-level optics --- antireflection nanostructure --- microlens array mold --- ultraprecision machining --- anodic aluminum oxide --- spatial uncertainty modeling --- additive manufacturing --- uncertainty quantification --- Image segmentation --- gaussian process modeling --- additive manufacturing --- selective laser melting --- surface roughness --- design of experiments --- Ti6Al4V --- SERS --- Surface-enhanced Raman scattering --- nanosphere array --- nanocone array --- hot embossing --- nanoimprinting --- plasma nitriding --- micro-nozzle --- micro-spring --- nitrogen supersaturation --- hardening --- hydrophobicity --- stiffness control --- product development --- conceptual design --- micro assembly --- data structure --- design for manufacturability --- low PC clinker --- Portland limestone ternary fiber–cement nanohybrids --- flexural strength --- TGA/dTG --- XRD --- MIP --- water impermeability tests --- micro and nano manufacturing --- micro-fluidics --- micro-optics --- micro and nano additive manufacturing --- micro-assembly --- surface engineering and interface nanotechnology --- micro factories --- micro reactors --- micro sensors --- micro actuators

Learning to Understand Remote Sensing Images

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ISBN: 9783038976844 9783038976851 Year: Volume: 1 Pages: 426 DOI: 10.3390/books978-3-03897-685-1 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Computer Science
Added to DOAB on : 2019-12-09 11:49:15
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With the recent advances in remote sensing technologies for Earth observation, many different remote sensors are collecting data with distinctive properties. The obtained data are so large and complex that analyzing them manually becomes impractical or even impossible. Therefore, understanding remote sensing images effectively, in connection with physics, has been the primary concern of the remote sensing research community in recent years. For this purpose, machine learning is thought to be a promising technique because it can make the system learn to improve itself. With this distinctive characteristic, the algorithms will be more adaptive, automatic, and intelligent. This book introduces some of the most challenging issues of machine learning in the field of remote sensing, and the latest advanced technologies developed for different applications. It integrates with multi-source/multi-temporal/multi-scale data, and mainly focuses on learning to understand remote sensing images. Particularly, it presents many more effective techniques based on the popular concepts of deep learning and big data to reach new heights of data understanding. Through reporting recent advances in the machine learning approaches towards analyzing and understanding remote sensing images, this book can help readers become more familiar with knowledge frontier and foster an increased interest in this field.

Keywords

hyperspectral image classification --- SELF --- SVMs --- Segment-Tree Filtering --- multi-sensor --- change feature analysis --- object-based --- multispectral images --- heterogeneous domain adaptation --- transfer learning --- multi-view canonical correlation analysis ensemble --- semi-supervised learning --- canonical correlation weighted voting --- ensemble learning --- image classification --- spatial attraction model (SAM) --- subpixel mapping (SPM) --- land cover --- mixed pixel --- spatial distribution --- hard classification --- building damage detection --- Fuzzy-GA decision making system --- machine learning techniques --- optical remotely sensed images --- sensitivity analysis --- texture analysis --- quality assessment --- ratio images --- Synthetic Aperture Radar (SAR) --- speckle --- speckle filters --- ice concentration --- SAR imagery --- convolutional neural network --- urban surface water extraction --- threshold stability --- sub-pixel --- linear spectral unmixing --- Landsat imagery --- image registration --- image fusion --- UAV --- metadata --- visible light and infrared integrated camera --- semantic segmentation --- CNN --- deep learning --- ISPRS --- remote sensing --- gate --- hyperspectral image --- sparse and low-rank graph --- tensor --- dimensionality reduction --- semantic labeling --- convolution neural network --- fully convolutional network --- sea-land segmentation --- ship detection --- hyperspectral image --- target detection --- multi-task learning --- sparse representation --- locality information --- remote sensing image correction --- color matching --- optimal transport --- CNN --- very high resolution images --- segmentation --- multi-scale clustering --- vehicle localization --- vehicle classification --- high resolution --- aerial image --- convolutional neural network (CNN) --- class imbalance --- deep learning --- convolutional neural network (CNN) --- fully convolutional network (FCN) --- classification --- remote sensing --- high resolution --- semantic segmentation --- deep convolutional neural networks --- manifold ranking --- single stream optimization --- high resolution image --- feature extraction --- hypergraph learning --- morphological profiles --- hyperedge weight estimation --- semantic labeling --- convolutional neural networks --- remote sensing --- deep learning --- aerial images --- hyperspectral image --- feature extraction --- dimensionality reduction --- optimized kernel minimum noise fraction (OKMNF) --- hyperspectral remote sensing --- endmember extraction --- multi-objective --- particle swarm optimization --- image alignment --- feature matching --- geostationary satellite remote sensing image --- GSHHG database --- Hough transform --- dictionary learning --- road detection --- Radon transform --- geo-referencing --- multi-sensor image matching --- Siamese neural network --- satellite images --- synthetic aperture radar --- inundation mapping --- flood --- optical sensors --- spatiotemporal context learning --- Modest AdaBoost --- HJ-1A/B CCD --- GF-4 PMS --- hyperspectral image classification --- automatic cluster number determination --- adaptive convolutional kernels --- hyperspectral imagery --- 1-dimensional (1-D) --- Convolutional Neural Network (CNN) --- Support Vector Machine (SVM) --- Random Forests (RF) --- machine learning --- deep learning --- TensorFlow --- multi-seasonal --- regional land cover --- saliency analysis --- remote sensing --- ROI detection --- hyperparameter sparse representation --- dictionary learning --- energy distribution optimizing --- multispectral imagery --- nonlinear classification --- kernel method --- dimensionality expansion --- deep convolutional neural networks --- road segmentation --- conditional random fields --- satellite images --- aerial images --- THEOS --- land cover change --- downscaling --- sub-pixel change detection --- machine learning --- MODIS --- Landsat --- very high resolution (VHR) satellite image --- topic modelling --- object-based image analysis --- image segmentation --- unsupervised classification --- multiscale representation --- GeoEye-1 --- wavelet transform --- fuzzy neural network --- remote sensing --- conservation --- urban heat island --- land surface temperature --- climate change --- land use --- land cover --- Landsat --- remote sensing --- SAR image --- despeckling --- dilated convolution --- skip connection --- residual learning --- scene classification --- saliency detection --- deep salient feature --- anti-noise transfer network --- DSFATN --- infrared image --- image registration --- MSER --- phase congruency --- hashing --- remote sensing image retrieval --- online learning --- hyperspectral image --- compressive sensing --- structured sparsity --- tensor sparse decomposition --- tensor low-rank approximation

Learning to Understand Remote Sensing Images

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ISBN: 9783038976981 9783038976998 Year: Volume: 2 Pages: 376 DOI: 10.3390/books978-3-03897-699-8 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Computer Science
Added to DOAB on : 2019-12-09 11:49:15
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Abstract

With the recent advances in remote sensing technologies for Earth observation, many different remote sensors are collecting data with distinctive properties. The obtained data are so large and complex that analyzing them manually becomes impractical or even impossible. Therefore, understanding remote sensing images effectively, in connection with physics, has been the primary concern of the remote sensing research community in recent years. For this purpose, machine learning is thought to be a promising technique because it can make the system learn to improve itself. With this distinctive characteristic, the algorithms will be more adaptive, automatic, and intelligent. This book introduces some of the most challenging issues of machine learning in the field of remote sensing, and the latest advanced technologies developed for different applications. It integrates with multi-source/multi-temporal/multi-scale data, and mainly focuses on learning to understand remote sensing images. Particularly, it presents many more effective techniques based on the popular concepts of deep learning and big data to reach new heights of data understanding. Through reporting recent advances in the machine learning approaches towards analyzing and understanding remote sensing images, this book can help readers become more familiar with knowledge frontier and foster an increased interest in this field.

Keywords

hyperspectral image classification --- SELF --- SVMs --- Segment-Tree Filtering --- multi-sensor --- change feature analysis --- object-based --- multispectral images --- heterogeneous domain adaptation --- transfer learning --- multi-view canonical correlation analysis ensemble --- semi-supervised learning --- canonical correlation weighted voting --- ensemble learning --- image classification --- spatial attraction model (SAM) --- subpixel mapping (SPM) --- land cover --- mixed pixel --- spatial distribution --- hard classification --- building damage detection --- Fuzzy-GA decision making system --- machine learning techniques --- optical remotely sensed images --- sensitivity analysis --- texture analysis --- quality assessment --- ratio images --- Synthetic Aperture Radar (SAR) --- speckle --- speckle filters --- ice concentration --- SAR imagery --- convolutional neural network --- urban surface water extraction --- threshold stability --- sub-pixel --- linear spectral unmixing --- Landsat imagery --- image registration --- image fusion --- UAV --- metadata --- visible light and infrared integrated camera --- semantic segmentation --- CNN --- deep learning --- ISPRS --- remote sensing --- gate --- hyperspectral image --- sparse and low-rank graph --- tensor --- dimensionality reduction --- semantic labeling --- convolution neural network --- fully convolutional network --- sea-land segmentation --- ship detection --- hyperspectral image --- target detection --- multi-task learning --- sparse representation --- locality information --- remote sensing image correction --- color matching --- optimal transport --- CNN --- very high resolution images --- segmentation --- multi-scale clustering --- vehicle localization --- vehicle classification --- high resolution --- aerial image --- convolutional neural network (CNN) --- class imbalance --- deep learning --- convolutional neural network (CNN) --- fully convolutional network (FCN) --- classification --- remote sensing --- high resolution --- semantic segmentation --- deep convolutional neural networks --- manifold ranking --- single stream optimization --- high resolution image --- feature extraction --- hypergraph learning --- morphological profiles --- hyperedge weight estimation --- semantic labeling --- convolutional neural networks --- remote sensing --- deep learning --- aerial images --- hyperspectral image --- feature extraction --- dimensionality reduction --- optimized kernel minimum noise fraction (OKMNF) --- hyperspectral remote sensing --- endmember extraction --- multi-objective --- particle swarm optimization --- image alignment --- feature matching --- geostationary satellite remote sensing image --- GSHHG database --- Hough transform --- dictionary learning --- road detection --- Radon transform --- geo-referencing --- multi-sensor image matching --- Siamese neural network --- satellite images --- synthetic aperture radar --- inundation mapping --- flood --- optical sensors --- spatiotemporal context learning --- Modest AdaBoost --- HJ-1A/B CCD --- GF-4 PMS --- hyperspectral image classification --- automatic cluster number determination --- adaptive convolutional kernels --- hyperspectral imagery --- 1-dimensional (1-D) --- Convolutional Neural Network (CNN) --- Support Vector Machine (SVM) --- Random Forests (RF) --- machine learning --- deep learning --- TensorFlow --- multi-seasonal --- regional land cover --- saliency analysis --- remote sensing --- ROI detection --- hyperparameter sparse representation --- dictionary learning --- energy distribution optimizing --- multispectral imagery --- nonlinear classification --- kernel method --- dimensionality expansion --- deep convolutional neural networks --- road segmentation --- conditional random fields --- satellite images --- aerial images --- THEOS --- land cover change --- downscaling --- sub-pixel change detection --- machine learning --- MODIS --- Landsat --- very high resolution (VHR) satellite image --- topic modelling --- object-based image analysis --- image segmentation --- unsupervised classification --- multiscale representation --- GeoEye-1 --- wavelet transform --- fuzzy neural network --- remote sensing --- conservation --- urban heat island --- land surface temperature --- climate change --- land use --- land cover --- Landsat --- remote sensing --- SAR image --- despeckling --- dilated convolution --- skip connection --- residual learning --- scene classification --- saliency detection --- deep salient feature --- anti-noise transfer network --- DSFATN --- infrared image --- image registration --- MSER --- phase congruency --- hashing --- remote sensing image retrieval --- online learning --- hyperspectral image --- compressive sensing --- structured sparsity --- tensor sparse decomposition --- tensor low-rank approximation

Algebraic Structures of Neutrosophic Triplets, Neutrosophic Duplets, or Neutrosophic Multisets

Authors: --- ---
ISBN: 9783038973843 Year: Volume: 1 Pages: 478 DOI: 10.3390/books978-3-03897-385-0 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General) --- Mathematics
Added to DOAB on : 2019-04-05 10:34:31
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Neutrosophy (1995) is a new branch of philosophy that studies triads of the form (, , ), where is an entity {i.e. element, concept, idea, theory, logical proposition, etc.}, is the opposite of , while is the neutral (or indeterminate) between them, i.e., neither nor .Based on neutrosophy, the neutrosophic triplets were founded, which have a similar form (x, neut(x), anti(x)), that satisfy several axioms, for each element x in a given set.This collective book presents original research papers by many neutrosophic researchers from around the world, that report on the state-of-the-art and recent advancements of neutrosophic triplets, neutrosophic duplets, neutrosophic multisets and their algebraic structures – that have been defined recently in 2016 but have gained interest from world researchers. Connections between classical algebraic structures and neutrosophic triplet / duplet / multiset structures are also studied. And numerous neutrosophic applications in various fields, such as: multi-criteria decision making, image segmentation, medical diagnosis, fault diagnosis, clustering data, neutrosophic probability, human resource management, strategic planning, forecasting model, multi-granulation, supplier selection problems, typhoon disaster evaluation, skin lesson detection, mining algorithm for big data analysis, etc.

Keywords

generalized aggregation operators --- interval neutrosophic set (INS) --- multi-attribute decision making (MADM) --- Choquet integral --- fuzzy measure --- clustering algorithm --- neutrosophic association rule --- data mining --- neutrosophic sets --- big data --- analytic hierarchy process (AHP) --- SWOT analysis --- multi-criteria decision-making (MCDM) techniques --- neutrosophic set theory --- neutrosophic clustering --- image segmentation --- neutrosophic c-means clustering --- region growing --- dermoscopy --- skin cancer --- neutosophic extended triplet subgroups --- neutrosophic triplet cosets --- neutrosophic triplet normal subgroups --- neutrosophic triplet quotient groups --- shopping mall --- photovoltaic plan --- decision-making trial and evaluation laboratory (DEMATEL) --- interval-valued neutrosophic set --- extended ELECTRE III --- symmetry --- single valued neutrosophic set (SVNS) --- neutrosophic multiset (NM) --- single valued neutrosophic multiset (SVNM) --- cosine measure --- multiple attribute decision-making --- LNGPBM operator --- LNGWPBM operator --- Linguistic neutrosophic sets --- generalized partitioned Bonferroni mean operator --- multiple attribute group decision-making (MAGDM) --- pseudo-BCI algebra --- hesitant fuzzy set --- neutrosophic set --- filter --- action learning --- school administrator --- SVM --- neutrosophic classification --- neutrosophic set --- soft set --- totally dependent-neutrosophic set --- totally dependent-neutrosophic soft set --- generalized De Morgan algebra --- complex neutrosophic set --- complex neutrosophic graph --- fuzzy graph --- matrix representation --- neutrosophic triplet groups --- semigroup --- semi-neutrosophic triplets --- classical group of neutrosophic triplets --- S-semigroup of neutrosophic triplets --- pseudo primitive elements --- neutrosophic sets (NSs) --- interval neutrosophic numbers (INNs) --- exponential operational laws of interval neutrosophic numbers --- interval neutrosophic weighted exponential aggregation (INWEA) operator --- multiple attribute decision making (MADM) --- typhoon disaster evaluation --- simplified neutrosophic linguistic numbers --- cloud model --- Maclaurin symmetric mean --- multi-criteria decision-making --- neutrosophy --- DSmT --- decision-making algorithms --- robotic dexterous hands --- grasping configurations --- grasp type --- generalized group --- neutrosophic triplet set --- neutrosophic triplet group --- group --- neutrosophic cubic set --- neutrosophic cubic graphs --- applications of neutrosophic cubic graphs --- single-valued neutrosophic multisets --- medical diagnosis --- probabilistic rough sets over two universes --- three-way decisions --- similarity measures --- neutrosophic cubic set --- decision-making --- soft sets --- support soft sets --- interval valued neutrosophic support soft sets --- sustainable supplier selection problems (SSSPs) --- analytic network process --- interdependency of criteria --- TOPSIS --- neutrosophic set --- 2ingle-valued neutrosophic set --- Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) --- integrated weight --- maximizing deviation --- multi-attribute decision-making (MADM) --- neutrosophic triplet set (NTS) --- partial metric spaces (PMS) --- fixed point theory (FPT) --- neutrosophic triplet --- quasi neutrosophic triplet loop --- quasi neutrosophic triplet group --- BE-algebra --- CI-algebra --- fuzzy time series --- forecasting --- two-factor fuzzy logical relationship --- multi-valued neutrosophic set --- Hamming distance --- neutrosophic set --- prioritized operator --- Muirhead mean --- multicriteria decision-making --- aggregation operators --- dual aggregation operators --- neutrosophic triplet group (NTG) --- NT-subgroup --- homomorphism theorem --- weak commutative neutrosophic triplet group --- neutrosophic rough set --- MGNRS --- dual domains --- inclusion relation --- decision-making --- neutro-monomorphism --- neutro-epimorphism --- neutro-automorphism --- fundamental neutro-homomorphism theorem --- first neutro-isomorphism theorem --- and second neutro-isomorphism theorem --- linear and non-linear neutrosophic number --- de-neutrosophication methods --- neutrosophic set --- bipolar fuzzy set --- neutrosophic bipolar fuzzy set --- neutrosophic bipolar fuzzy weighted averaging operator --- similarity measure --- algorithm --- multiple attribute decision making problem --- neutrosophic duplets --- semigroup --- neutrosophic triplet groups --- neutrosophic set --- fault diagnosis --- normal distribution --- defuzzification --- simplified neutrosophic weighted averaging operator --- (commutative) ideal --- generalized neutrosophic set --- generalized neutrosophic ideal --- commutative generalized neutrosophic ideal --- linguistic neutrosophic sets --- multi-criteria group decision-making --- power aggregation operator --- extended TOPSIS method --- probabilistic single-valued (interval) neutrosophic hesitant fuzzy set --- multi-attribute decision making --- aggregation operator --- quasigroup --- loop --- BCI-algebra --- Bol-Moufang --- quasi neutrosophic loops --- Fenyves identities --- G-metric --- neutrosophic G-metric --- neutrosophic sets --- clustering --- neutrosophic big data --- neutrosophic logic --- aggregation operator --- complement --- intersection --- membership --- neutrosophic soft set --- NC power dual MM operator (NCPDMM) operator --- NCPMM operator --- MADM --- MM operator --- Neutrosophic cubic sets --- PA operator --- interval neutrosophic sets --- Bonferroni mean --- power operator --- multi-attribute decision making (MADM) --- multiple attribute group decision making (MAGDM) --- 2-tuple linguistic neutrosophic sets (2TLNSs) --- TODIM model --- 2TLNNs TODIM method --- construction project --- MCGDM problems --- triangular fuzzy neutrosophic sets (TFNSs) --- VIKOR model --- TFNNs VIKOR method --- potential evaluation --- emerging technology commercialization --- Q-linguistic neutrosophic variable set --- vector similarity measure --- cosine measure --- Dice measure --- Jaccard measure --- decision making --- inclusion relation --- neutrosophic rough set --- multi-attribute group decision-making (MAGDM) --- multigranulation neutrosophic rough set (MNRS) --- two universes --- single valued trapezoidal neutrosophic number --- multi-criteria group decision making --- possibility degree --- power aggregation operators --- LA-semihypergroups --- neutrosophic triplet set --- neutro-homomorphism --- algorithm --- decision making --- expert set --- generalized neutrosophic set --- neutrosophic sets --- Q-neutrosophic --- soft sets --- simplified neutrosophic sets (SNSs) --- interval number --- dependent degree --- multi-criteria group decision-making (MCGDM) --- computability --- oracle Turing machines --- neutrosophic sets --- neutrosophic logic --- recursive enumerability --- oracle computation --- criterion functions --- neutrosophic computation --- neutrosophic logic --- quantum computation --- computation --- logic

Algebraic Structures of Neutrosophic Triplets, Neutrosophic Duplets, or Neutrosophic Multisets

Authors: --- ---
ISBN: 9783038974758 Year: Volume: 2 Pages: 450 DOI: 10.3390/books978-3-03897-476-5 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General) --- Mathematics
Added to DOAB on : 2019-04-05 10:34:31
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Abstract

Neutrosophy (1995) is a new branch of philosophy that studies triads of the form (, , ), where is an entity {i.e. element, concept, idea, theory, logical proposition, etc.}, is the opposite of , while is the neutral (or indeterminate) between them, i.e., neither nor .Based on neutrosophy, the neutrosophic triplets were founded, which have a similar form (x, neut(x), anti(x)), that satisfy several axioms, for each element x in a given set.This collective book presents original research papers by many neutrosophic researchers from around the world, that report on the state-of-the-art and recent advancements of neutrosophic triplets, neutrosophic duplets, neutrosophic multisets and their algebraic structures – that have been defined recently in 2016 but have gained interest from world researchers. Connections between classical algebraic structures and neutrosophic triplet / duplet / multiset structures are also studied. And numerous neutrosophic applications in various fields, such as: multi-criteria decision making, image segmentation, medical diagnosis, fault diagnosis, clustering data, neutrosophic probability, human resource management, strategic planning, forecasting model, multi-granulation, supplier selection problems, typhoon disaster evaluation, skin lesson detection, mining algorithm for big data analysis, etc.

Keywords

generalized aggregation operators --- interval neutrosophic set (INS) --- multi-attribute decision making (MADM) --- Choquet integral --- fuzzy measure --- clustering algorithm --- neutrosophic association rule --- data mining --- neutrosophic sets --- big data --- analytic hierarchy process (AHP) --- SWOT analysis --- multi-criteria decision-making (MCDM) techniques --- neutrosophic set theory --- neutrosophic clustering --- image segmentation --- neutrosophic c-means clustering --- region growing --- dermoscopy --- skin cancer --- neutosophic extended triplet subgroups --- neutrosophic triplet cosets --- neutrosophic triplet normal subgroups --- neutrosophic triplet quotient groups --- shopping mall --- photovoltaic plan --- decision-making trial and evaluation laboratory (DEMATEL) --- interval-valued neutrosophic set --- extended ELECTRE III --- symmetry --- single valued neutrosophic set (SVNS) --- neutrosophic multiset (NM) --- single valued neutrosophic multiset (SVNM) --- cosine measure --- multiple attribute decision-making --- LNGPBM operator --- LNGWPBM operator --- Linguistic neutrosophic sets --- generalized partitioned Bonferroni mean operator --- multiple attribute group decision-making (MAGDM) --- pseudo-BCI algebra --- hesitant fuzzy set --- neutrosophic set --- filter --- action learning --- school administrator --- SVM --- neutrosophic classification --- neutrosophic set --- soft set --- totally dependent-neutrosophic set --- totally dependent-neutrosophic soft set --- generalized De Morgan algebra --- complex neutrosophic set --- complex neutrosophic graph --- fuzzy graph --- matrix representation --- neutrosophic triplet groups --- semigroup --- semi-neutrosophic triplets --- classical group of neutrosophic triplets --- S-semigroup of neutrosophic triplets --- pseudo primitive elements --- neutrosophic sets (NSs) --- interval neutrosophic numbers (INNs) --- exponential operational laws of interval neutrosophic numbers --- interval neutrosophic weighted exponential aggregation (INWEA) operator --- multiple attribute decision making (MADM) --- typhoon disaster evaluation --- simplified neutrosophic linguistic numbers --- cloud model --- Maclaurin symmetric mean --- multi-criteria decision-making --- neutrosophy --- DSmT --- decision-making algorithms --- robotic dexterous hands --- grasping configurations --- grasp type --- generalized group --- neutrosophic triplet set --- neutrosophic triplet group --- group --- neutrosophic cubic set --- neutrosophic cubic graphs --- applications of neutrosophic cubic graphs --- single-valued neutrosophic multisets --- medical diagnosis --- probabilistic rough sets over two universes --- three-way decisions --- similarity measures --- neutrosophic cubic set --- decision-making --- soft sets --- support soft sets --- interval valued neutrosophic support soft sets --- sustainable supplier selection problems (SSSPs) --- analytic network process --- interdependency of criteria --- TOPSIS --- neutrosophic set --- 2ingle-valued neutrosophic set --- Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) --- integrated weight --- maximizing deviation --- multi-attribute decision-making (MADM) --- neutrosophic triplet set (NTS) --- partial metric spaces (PMS) --- fixed point theory (FPT) --- neutrosophic triplet --- quasi neutrosophic triplet loop --- quasi neutrosophic triplet group --- BE-algebra --- CI-algebra --- fuzzy time series --- forecasting --- two-factor fuzzy logical relationship --- multi-valued neutrosophic set --- Hamming distance --- neutrosophic set --- prioritized operator --- Muirhead mean --- multicriteria decision-making --- aggregation operators --- dual aggregation operators --- neutrosophic triplet group (NTG) --- NT-subgroup --- homomorphism theorem --- weak commutative neutrosophic triplet group --- neutrosophic rough set --- MGNRS --- dual domains --- inclusion relation --- decision-making --- neutro-monomorphism --- neutro-epimorphism --- neutro-automorphism --- fundamental neutro-homomorphism theorem --- first neutro-isomorphism theorem --- and second neutro-isomorphism theorem --- linear and non-linear neutrosophic number --- de-neutrosophication methods --- neutrosophic set --- bipolar fuzzy set --- neutrosophic bipolar fuzzy set --- neutrosophic bipolar fuzzy weighted averaging operator --- similarity measure --- algorithm --- multiple attribute decision making problem --- neutrosophic duplets --- semigroup --- neutrosophic triplet groups --- neutrosophic set --- fault diagnosis --- normal distribution --- defuzzification --- simplified neutrosophic weighted averaging operator --- (commutative) ideal --- generalized neutrosophic set --- generalized neutrosophic ideal --- commutative generalized neutrosophic ideal --- linguistic neutrosophic sets --- multi-criteria group decision-making --- power aggregation operator --- extended TOPSIS method --- probabilistic single-valued (interval) neutrosophic hesitant fuzzy set --- multi-attribute decision making --- aggregation operator --- quasigroup --- loop --- BCI-algebra --- Bol-Moufang --- quasi neutrosophic loops --- Fenyves identities --- G-metric --- neutrosophic G-metric --- neutrosophic sets --- clustering --- neutrosophic big data --- neutrosophic logic --- aggregation operator --- complement --- intersection --- membership --- neutrosophic soft set --- NC power dual MM operator (NCPDMM) operator --- NCPMM operator --- MADM --- MM operator --- Neutrosophic cubic sets --- PA operator --- interval neutrosophic sets --- Bonferroni mean --- power operator --- multi-attribute decision making (MADM) --- multiple attribute group decision making (MAGDM) --- 2-tuple linguistic neutrosophic sets (2TLNSs) --- TODIM model --- 2TLNNs TODIM method --- construction project --- MCGDM problems --- triangular fuzzy neutrosophic sets (TFNSs) --- VIKOR model --- TFNNs VIKOR method --- potential evaluation --- emerging technology commercialization --- Q-linguistic neutrosophic variable set --- vector similarity measure --- cosine measure --- Dice measure --- Jaccard measure --- decision making --- inclusion relation --- neutrosophic rough set --- multi-attribute group decision-making (MAGDM) --- multigranulation neutrosophic rough set (MNRS) --- two universes --- single valued trapezoidal neutrosophic number --- multi-criteria group decision making --- possibility degree --- power aggregation operators --- LA-semihypergroups --- neutrosophic triplet set --- neutro-homomorphism --- algorithm --- decision making --- expert set --- generalized neutrosophic set --- neutrosophic sets --- Q-neutrosophic --- soft sets --- simplified neutrosophic sets (SNSs) --- interval number --- dependent degree --- multi-criteria group decision-making (MCGDM) --- computability --- oracle Turing machines --- neutrosophic sets --- neutrosophic logic --- recursive enumerability --- oracle computation --- criterion functions --- neutrosophic computation --- neutrosophic logic --- quantum computation --- computation --- logic --- n/a

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