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Vision, image and machine learning (partie AM)

The foundations of Deep Learning for images #

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Le Cours #

  • CM1: Introduction to neural networks (forward and backpropagation)
  • CM2: Convolution Neural Networks (CNN)
  • CM3: Auto-encoder (AE), processing skeleton data, introduction to generative approaches (basic GAN)
  • CM4: the “modern” vision (Segmentation, Tracking-YOLO, Transformer for Images)

Tutorials (TP) #

  1. Installation
  2. A neural network from scratch. (Python, numpy)
  3. Classification
    1. 2D Point Classification. (Pytorch) (If you follow the Master’s Course, go directly to question 2.2 or 3)
    2. Image classification using Convolution Neural Networks. (CNN, Pytorch)
  4. Style transfer between images. (Pytorch)
  5. Gesture transfer and person image generation