Integrating Flexible Normalization into Midlevel Representations of Deep Convolutional Neural Networks

Volume: 31, Issue: 11, Pages: 2138 - 2176
Published: Nov 1, 2019
Abstract
Deep convolutional neural networks (CNNs) are becoming increasingly popular models to predict neural responses in visual cortex. However, contextual effects, which are prevalent in neural processing and in perception, are not explicitly handled by current CNNs, including those used for neural prediction. In primary visual cortex, neural responses are modulated by stimuli spatially surrounding the classical receptive field in rich ways. These...
Paper Details
Title
Integrating Flexible Normalization into Midlevel Representations of Deep Convolutional Neural Networks
Published Date
Nov 1, 2019
Volume
31
Issue
11
Pages
2138 - 2176
Citation AnalysisPro
  • Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
  • Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.