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The document outlines key concepts and models in computer vision, including CNN architectures like AlexNet, VGG16, and ResNet, as well as segmentation and object detection techniques such as U-Net and YOLO. It also covers diffusion-based models for generative tasks, NLP techniques including RNNs and Transformers, and important concepts in LLMs like LORA and MoEs. Additionally, it suggests exploring 3D reconstruction methods like NERF and Gaussian splatting while encouraging project-based learning in deep ne

Author

pas081bct037

Language

EN