Episode 09: Drew Linsley, Brown, on inductive biases for vision and generalization
Generally Intelligent
00:00
Redefining Motion Recognition in Neural Networks
This chapter explores the challenges of synchrony in neural activity and its implications for motion perception in visual systems. It critiques existing 3D convolution models and advocates for more innovative approaches to motion recognition, examining the role of attentional mechanisms and biases in machine vision. The discussion highlights the need for new benchmarks and data generation methods to advance understanding in machine learning and neuroscience.
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