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Feature Detection in Computer Vision

 * Introduction
 * Feature (computer vision)


 * Feature Detection
 * Feature detection (computer vision)
 * Corner detection
 * Edge (geometry)
 * Edge detection
 * Sobel operator
 * Canny edge detector
 * Features from accelerated segment test
 * Difference of Gaussians
 * Ridge detection
 * Blob detection
 * Interest point detection
 * Principal curvature-based region detector
 * Maximally stable extremal regions
 * Scale-invariant feature transform
 * GLOH
 * SURF
 * LESH


 * Feature Extraction
 * Feature extraction
 * Color histogram
 * Principal component analysis
 * Semidefinite embedding
 * Multifactor dimensionality reduction
 * Multilinear subspace learning
 * Nonlinear dimensionality reduction
 * Isomap
 * Kernel principal component analysis
 * Latent semantic analysis
 * Partial least squares regression
 * Independent component analysis
 * Autoencoder
 * Recurrent neural network
 * Motion detection
 * Optical flow
 * Hough transform
 * Thresholding (image processing)
 * Connected-component labeling
 * Graphical model
 * Template matching


 * Feature Learning
 * Feature learning
 * K-means clustering
 * Restricted Boltzmann machine
 * Semi-supervised learning
 * Artificial neural network
 * Basis function
 * Radial basis function network
 * Kernel method
 * Vector quantization
 * Statistical classification
 * Derivative
 * Gaussian blur
 * Scale space
 * Scale space implementation
 * Jet (mathematics)
 * N-jet
 * Image tracing
 * Neighborhood operation
 * Boolean data type


 * Deep Learning
 * Deep learning
 * Convolutional neural network
 * Deep belief network
 * Propositional formula


 * Feature Selection
 * Feature selection
 * Simulated annealing
 * Genetic algorithm
 * Greedy algorithm
 * Targeted projection pursuit
 * Random forest
 * Decision tree learning
 * Memetic algorithm
 * Minimum redundancy feature selection


 * Cluster Analysis
 * Cluster analysis
 * Hierarchical clustering
 * Basic sequential algorithmic scheme
 * Davies–Bouldin index
 * Dunn index
 * Silhouette (clustering)
 * Rand index
 * F1 score
 * Jaccard index
 * Fowlkes–Mallows index
 * Mutual information
 * Confusion matrix
 * Clustering high-dimensional data
 * Conceptual clustering
 * Consensus clustering
 * Constrained clustering
 * Data stream clustering
 * Sequence clustering
 * Spectral clustering
 * Nearest neighbor search
 * Neighbourhood components analysis
 * Latent class model
 * Multidimensional scaling
 * Cluster-weighted modeling
 * Determining the number of clusters in a data set
 * Parallel coordinates
 * Structured data analysis (statistics)


 * Dimensionality Reduction
 * Dimensionality reduction
 * Curse of dimensionality
 * Data mining


 * Image Segmentation
 * Image segmentation
 * Balanced histogram thresholding
 * Watershed (image processing)
 * Scale-space segmentation
 * Range segmentation
 * Image-based meshing
 * Quantization (image processing)
 * Color quantization