Discussion: Modeling Visual Cortex V4 in Naturalistic Conditions with Invariant and Sparse Image Representations Ping Li Department of Statistics and Biostatistics.

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Discussion: Modeling Visual Cortex V4 in Naturalistic Conditions with Invariant and Sparse Image Representations Ping Li Department of Statistics and Biostatistics Department of Computer Science Rutgers University May 2, 2014

Picture from Simon Thorpe

Question (Curiosity) #1 The input images are, by default, dense. Are there firm scientific evidences that human brains process visual signals through a sparse and low-rank mechanism? If so, then do we know, at which layer, an input image becomes a sparse signal: retina, V1, V2, V4…?

Question (Curiosity) #2 The talk mentioned Deep Learning as future work. Are there more concrete thoughts & research plans? For example, will the current multi-layer invariant feature extractor be replaced by an automatic feature learner? How many layers are reasonable for this task? 10? Are there firm biological evidence that the human visual system functions as a deep architecture? If so, is there intuition why “human/brain computers” are so fast while deep learning can take months of GPU time?

Thank you and other questions from audience?