Poster 1

The poster presents a study where task-optimized convolutional neural networks (CNNs) challenge the expertise hypothesis, suggesting that systems broadly optimized for object recognition provide a better foundation for learning fine-grained tasks like car discrimination than systems optimized for face recognition, thus questioning the computational viability of the expertise hypothesis.

For more detailed information, please Checkout the poster.