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IEEEICCI
2009
IEEE
9 years 7 months ago
Learning from an ensemble of Receptive Fields
Abstract-In this paper, we construct a neural-inspired computational model based on the representational capabilities of receptive fields. The proposed model, known as Shape Encodi...
Hanlin Goh, Joo Hwe Lim, Chai Quek
NECO
1998
168views more  NECO 1998»
9 years 9 months ago
Constructive Incremental Learning from Only Local Information
We introduce a constructive, incremental learning system for regression problems that models data by means of spatially localized linear models. In contrast to other approaches, t...
Stefan Schaal, Christopher G. Atkeson
COGSCI
2004
76views more  COGSCI 2004»
9 years 9 months ago
Reverse correlation in neurophysiology
This article presents a review of reverse correlation in neurophysiology. We discuss the basis of reverse correlation in linear transducers and in spiking neurons. The application...
Dario L. Ringach, Robert Shapley
BC
2004
86views more  BC 2004»
9 years 9 months ago
Is sparse and distributed the coding goal of simple cells?
Abstract. The question of why the receptive fields of simple cells in the primary visual cortex are Gabor-like is a crucial one in vision research. Many research efforts (Olshausen...
Li Zhao
NIPS
1990
9 years 10 months ago
Learning to See Rotation and Dilation with a Hebb Rule
Previous work (M.I. Sereno, 1989; cf. M.E. Sereno, 1987) showed that a feedforward network with area V1-like input-layer units and a Hebb rule can develop area MT-like second laye...
Martin I. Sereno, Margaret E. Sereno
ESANN
2003
9 years 11 months ago
RetinotopicNET: An Efficient Simulator for Retinotopic Visual Architectures
: -RetinotopicNET is an efficient simulator for neural networks with retinotopic-like receptive fields. The system has two main characteristics: it is event-driven and it takes adv...
Raul Cristian Muresan
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