The next Cognitive brown bag speaker will be Thomas Serre of Brown University (http://serre-lab.clps.brown.edu/). The talk is on Wednesday 2/13, 12:00, Tobin 521B; title and abstract are below.

What are the computations underlying primate versus machine vision?

Primates excel at object recognition: For decades, the speed and accuracy of their visual system have remained unmatched by computer algorithms. But recent advances in Deep Convolutional Networks (DCNs) have led to vision systems that are starting to rival human decisions. A growing body of work also suggests that this recent surge in accuracy is accompanied by a concomitant improvement in our ability to account for neural data in higher areas of the primate visual cortex. Overall, DCNs have become de facto computational models of visual recognition.

In this talk, I will review recent work by our group which brings into relief limitations of modern DCNs as computational models of primate vision. I will show that DCNs are limited in their ability to solve seemingly simple visual reasoning problems involving incremental grouping, similarity and spatial relation judgments suggesting the need for additional neural computations beyond those implemented in current architectures. I will further demonstrate how neuroscience principles may help guide the future design for more robust computer vision architectures.