CV-410: Convolutional Neural Networks for Vision

Course Description

Deep learning for image understanding. CNN architectures: AlexNet through EfficientNet and ConvNeXt. Object detection: YOLO family, Faster R-CNN, DETR. Image segmentation: FCN, U-Net, Mask R-CNN. Transfer learning and domain adaptation. Data augmentation strategies. The shift from CNNs to ViTs and hybrid architectures. Students implement and train detection models on custom datasets.