Explores Convolutional Neural Networks for semantic segmentation, discussing models for pixel classification, learned decoding, and the importance of skip connections.
Explores the evolution of visual intelligence models, focusing on Transformers and their applications in computer vision and natural language processing.
Delves into the geometric insights of deep learning models, exploring their vulnerability to perturbations and the importance of robustness and interpretability.