Sakai et al., 2000 - Google Patents
Spatial pooling in the second-order spatial structure of cortical complex cellsSakai et al., 2000
View HTML- Document ID
- 7036169035808405139
- Author
- Sakai K
- Tanaka S
- Publication year
- Publication venue
- Vision Research
External Links
Snippet
We investigate what computational mechanisms give rise to the nonlinearity of complex cell responses in the primary visual cortex. Complex cells are characterized by their nonlinear spatial properties such as spatial phase invariance and nonlinear spatial additivity. We …
- 238000011176 pooling 0 title abstract description 58
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computer systems based on biological models
- G06N3/02—Computer systems based on biological models using neural network models
- G06N3/06—Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons
- G06N3/063—Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons using electronic means
- G06N3/0635—Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons using electronic means using analogue means
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/36—Image preprocessing, i.e. processing the image information without deciding about the identity of the image
- G06K9/46—Extraction of features or characteristics of the image
- G06K9/4604—Detecting partial patterns, e.g. edges or contours, or configurations, e.g. loops, corners, strokes, intersections
- G06K9/4609—Detecting partial patterns, e.g. edges or contours, or configurations, e.g. loops, corners, strokes, intersections by matching or filtering
- G06K9/4619—Biologically-inspired filters, e.g. receptive fields
- G06K9/4623—Biologically-inspired filters, e.g. receptive fields with interaction between the responses of different filters
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computer systems based on biological models
- G06N3/02—Computer systems based on biological models using neural network models
- G06N3/04—Architectures, e.g. interconnection topology
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
- G06K9/6232—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods
- G06K9/6247—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods based on an approximation criterion, e.g. principal component analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
- G06K9/6232—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods
- G06K9/6251—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods based on a criterion of topology preservation, e.g. multidimensional scaling, self-organising maps
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/00221—Acquiring or recognising human faces, facial parts, facial sketches, facial expressions
- G06K9/00268—Feature extraction; Face representation
- G06K9/00281—Local features and components; Facial parts ; Occluding parts, e.g. glasses; Geometrical relationships
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/40—Analysis of texture
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10024—Color image
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/16—Matrix or vector computation, e.g. matrix-matrix or matrix-vector multiplication, matrix factorization
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/15—Correlation function computation including computation of convolution operations
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Sakai et al. | Spatial pooling in the second-order spatial structure of cortical complex cells | |
Spratling | Predictive coding as a model of response properties in cortical area V1 | |
Lai et al. | A neural implementation of canonical correlation analysis | |
Itti et al. | Comparison of feature combination strategies for saliency-based visual attention systems | |
EinhaÈuser et al. | Learning the invariance properties of complex cells from their responses to natural stimuli | |
Hyvärinen et al. | A two-layer sparse coding model learns simple and complex cell receptive fields and topography from natural images | |
Itti et al. | A saliency-based search mechanism for overt and covert shifts of visual attention | |
Wilson | Non-Fourier cortical processes in texture, form, and motion perception | |
Zhaoping | V1 mechanisms and some figure–ground and border effects | |
Spratling | Predictive coding accounts for V1 response properties recorded using reverse correlation | |
VanRullen et al. | Feed-forward contour integration in primary visual cortex based on asynchronous spike propagation | |
Bruce | Features that draw visual attention: an information theoretic perspective | |
Zabbah et al. | The impact of the lateral geniculate nucleus and corticogeniculate interactions on efficient coding and higher-order visual object processing | |
Joukes et al. | Motion detection based on recurrent network dynamics | |
Roy et al. | Spatial information transfer in hippocampal place cells depends on trial-to-trial variability, symmetry of place-field firing, and biophysical heterogeneities | |
Molin et al. | Proto-object based visual saliency model with a motion-sensitive channel | |
Wang et al. | Contour detection in colour images using a neurophysiologically inspired model | |
Wiltschut et al. | Efficient coding correlates with spatial frequency tuning in a model of V1 receptive field organization | |
Bonneh et al. | Quantification of local symmetry: application to texture discrimination | |
Kallel et al. | Bootstrap for neural model selection | |
Ontrup et al. | Perceptual grouping in a neural model: Reproducing human texture perception | |
McManus et al. | A computational model of perceptual fill-in following retinal degeneration | |
Alexander et al. | Generalization of learning by synchronous waves: from perceptual organization to invariant organization | |
du Buf | Improved grating and bar cell models in cortical area V1 and texture coding | |
Cios et al. | Networks of spiking neurons in modeling and problem solving |