A high-throughput screening approach to discovering good forms of biologically inspired visual representation
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Invariant visual object recognition and shape processing in ratsThe Invariance Hypothesis Implies Domain-Specific Regions in Visual CortexEvaluation and optimization for liquid-based preparation cytology in whole slide imagingQuantifying Repetitive Transmission at Chemical Synapses: A Generative-Model ApproachImagenet classification with deep convolutional neural networksPerceptual spaces: mathematical structures to neural mechanisms.Exploiting graphics processing units for computational biology and bioinformatics.An efficient automated parameter tuning framework for spiking neural networksPerformance-optimized hierarchical models predict neural responses in higher visual cortex.Factorial comparison of working memory modelsRobust action recognition using multi-scale spatial-temporal concatenations of local features as natural action structures.Top-down feedback in an HMAX-like cortical model of object perception based on hierarchical Bayesian networks and belief propagationDeep neural networks rival the representation of primate IT cortex for core visual object recognition.Accelerating Computation of DCM for ERP in MATLAB by External Function Calls to the GPUMulti-scale spatial concatenations of local features in natural scenes and scene classificationPattern recognition algorithm reveals how birds evolve individual egg pattern signatures.Explaining the Timing of Natural Scene Understanding with a Computational Model of Perceptual Categorization.How does the brain solve visual object recognition?Balanced increases in selectivity and tolerance produce constant sparseness along the ventral visual streamRecurrent Processing during Object RecognitionCompressive spatial summation in human visual cortex.Vision: are models of object recognition catching up with the brain?Using goal-driven deep learning models to understand sensory cortex.Models of visual categorization.Is realistic neuronal modeling realistic?Finding and recognizing objects in natural scenes: complementary computations in the dorsal and ventral visual systems.Object recognition with hierarchical discriminant saliency networks.Invariant visual object recognition: biologically plausible approaches.Computer-aided assessment of breast density: comparison of supervised deep learning and feature-based statistical learning.Semantic category-based decoding of human brain activity using a Gabor-based model by estimating intracranial field potential range in temporal cortex.Tuning and spontaneous spike time synchrony share a common structure in macaque inferior temporal cortex.Suitability of V1 energy models for object classification.Using human brain activity to guide machine learning.An Insight into Extreme Learning Machines: Random Neurons, Random Features and Kernels
P2860
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P2860
A high-throughput screening approach to discovering good forms of biologically inspired visual representation
description
2009 nî lūn-bûn
@nan
2009 թուականի Նոյեմբերին հրատարակուած գիտական յօդուած
@hyw
2009 թվականի նոյեմբերին հրատարակված գիտական հոդված
@hy
2009年の論文
@ja
2009年論文
@yue
2009年論文
@zh-hant
2009年論文
@zh-hk
2009年論文
@zh-mo
2009年論文
@zh-tw
2009年论文
@wuu
name
A high-throughput screening ap ...... inspired visual representation
@ast
A high-throughput screening ap ...... inspired visual representation
@en
A high-throughput screening ap ...... inspired visual representation
@nl
type
label
A high-throughput screening ap ...... inspired visual representation
@ast
A high-throughput screening ap ...... inspired visual representation
@en
A high-throughput screening ap ...... inspired visual representation
@nl
prefLabel
A high-throughput screening ap ...... inspired visual representation
@ast
A high-throughput screening ap ...... inspired visual representation
@en
A high-throughput screening ap ...... inspired visual representation
@nl
P2093
P2860
P1476
A high-throughput screening ap ...... inspired visual representation
@en
P2093
David D Cox
David Doukhan
James J DiCarlo
Nicolas Pinto
P2860
P304
P356
10.1371/JOURNAL.PCBI.1000579
P407
P577
2009-11-01T00:00:00Z