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If we can make computers play chess and even Jeopardy, then why can't we make them see like us?
This is a particularly perplexing question when we consider how easy we find the act of seeing which we perform countless times each day with virtually no errors.
What makes vision such a hard problem? How does the brain accomplish vision? To answer these questions we are recording brain signals at multiple scales to understand how the brain is solving this problem and using these data to improve computer vision.
In this webinar, we will be describing some of the recent findings elucidating object recognition at the behavioral, neuronal, and computational levels.
SP Arun received his B.Tech from IIT Bombay, and MS & PhD from Johns Hopkins University, all in Electrical Engineering. He completed his postdoctoral research at Carnegie Mellon University and joined the Centre for Neuroscience at IISc where he is currently an Associate Professor. He is fascinated by how the brain transforms sensations into perception.
For more details visit the homepage of his research group, the Vision Lab @ IISc. https://sites.google.com/site/visionlabiisc/