Biological Vision

Biological vision research aims to understand how animals, particularly primates, process visual information, often using computational models to test hypotheses about underlying mechanisms. Current research focuses on developing and evaluating biologically-inspired artificial neural networks, including convolutional neural networks (CNNs), vision transformers (ViTs), and spiking neural networks (SNNs), often incorporating concepts like retinotopic mapping, saccades, and generative models to improve performance and robustness. These efforts are significant because they not only advance our understanding of the brain but also lead to more efficient and robust computer vision systems with applications in diverse fields like medical imaging and robotics.