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cvpr_23_24_spring's Introduction

CVPR_23_24_Spring

  1. Module Zero (0)
    1. Course Overview
    2. Software installation
    3. Programming basics in python
    4. Built-in data structures / Collections in python
    5. Numpy
    6. Lambda, Map, Reduce, Filter
    7. Matplotlib
  2. Module One (1)
    1. Perceptron
    2. Activation functions
    3. Neural Network architectures
    4. Convolutional Neural Network architectures
  3. Module Two (2)
    1. Neural Network with Tensorflow & Keras (MNIST digits classification)
    2. Convolutional Neural Network with Tensorflow & Keras (CIFAR-10 dataset classification)
      • Saving and Loading a Keras Neural Network
      • Early Stopping in Keras to Prevent Overfitting
    3. Image classification with custom dataset
  4. Module Three (3)
    1. Image classification with AlexNet
    2. Image classification with VggNet
  5. Module Four (4)
    1. Image classification with ResNet
    2. Image classification with Inception: GoogleNet
  6. Module Five (5)
    1. Transfer Learning
    2. Visualization of learned karnels
  7. Module Six (6)
    1. Object detection Using Faster R-CNN
  8. Module Seven (7)
    1. Object detection Using SSD
    2. Object detection Using YOLO
  9. Module Eight (8)
    1. Segmentation using UNet
  10. Module Nine (9)
    1. GAN

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