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As the ultimate information processing device, the brain naturally lends itself to being studied with information theory. The application of information theory to neuroscience has spurred the development of principled theories of brain function, and has led to advances in the study of consciousness, as well as to the development of analytical techniques to crack the neural code—that is, to unveil the language used by neurons to encode and process information. In particular, advances in experimental techniques enabling the precise recording and manipulation of neural activity on a large scale now enable for the first time the precise formulation and the quantitative testing of hypotheses about how the brain encodes and transmits the information used for specific functions across areas. This Special Issue presents twelve original contributions on novel approaches in neuroscience using information theory, and on the development of new information theoretic results inspired by problems in neuroscience.

neural network --- Potts model --- latching --- recursion --- functional connectome --- graph theoretical analysis --- eigenvector centrality --- orderness --- network eigen-entropy --- information entropy production --- discrete Markov chains --- spike train statistics --- Gibbs measures --- maximum entropy principle --- pulse-gating --- channel capacity --- neural coding --- feedforward networks --- neural information propagation --- information theory --- mutual information decomposition --- synergy --- redundancy --- integrated information theory --- integrated information --- minimum information partition --- submodularity --- Queyranne’s algorithm --- consciousness --- maximum entropy --- higher-order correlations --- neural population coding --- Ising model --- brain network --- complex networks --- connectome --- information theory --- graph theory --- free-energy principle --- internal model hypothesis --- unconscious inference --- infomax principle --- independent component analysis --- principal component analysis --- goodness --- categorical perception --- perceptual magnet --- information theory --- perceived similarity --- mutual information --- synergy --- redundancy --- neural code --- hippocampus --- entorhinal cortex --- navigation --- neural code --- representation --- decoding --- spike-time precision --- discrimination --- noise correlations --- information theory --- mismatched decoding --- information theory --- neuroscience

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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.

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