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dl_cv_tensorflow_10weeks

딥러닝-영상인식 CAMP 10주 과정을 위한 TensorFlow 코드들

Week1 - Deep Learning Introduction

  • MNIST Classification using Softmax Regression 😄 (Code)
  • MNIST Reconstruction using Autoencoder (Code)
  • MNIST Classification using Artificial Neural Networks(ANN) (Code)
  • MNIST Classification using Stacked Autoencoders + Softmax Classifier (Code)

Week2 - Convolutional Neural Networks(CNNs)

  • MNIST Classification using Convolutional Neural Networks(CNNs) (Code)
  • MNIST Classification using Convolutional Neural Networks(CNNs) with tf.train.Saver() (Code)
  • CIFAR-10 Image Classification using Convolutional Neural Networks(CNNs) (Code)
  • CIFAR-10 Image Classification using Convolutional Neural Networks(CNNs) 😄 (Code)
  • Custom Dataset Image Classification using Inception v3 Retraining(Fine-Tuning) (Code)

Week3 - Recurrent Neural Networks(RNNs)

  • Embedding Example (Code)
  • Gradient Clipping Example (Code)
  • Character-level Language Modeling using Recurrent Neural Networks(RNNs) (Char-RNN) 😄 (Code)
  • Character-level Language Modeling using Recurrent Neural Networks(RNNs) (Char-RNN) (Code)
  • Character-level Language Modeling using Recurrent Neural Networks(RNNs) (Char-RNN) using tf.nn.dynamic_rnn (Code)
  • Penn Tree Bank(PTB) Dataset Language Modeling using Recurrent Neural Networks(RNNs) (Code)
  • Penn Tree Bank(PTB) Dataset Language Modeling using Recurrent Neural Networks(RNNs) using tf.nn.dynamic_rnn (Code)

Week4 - Natural Language Processing(NLP) QA & Visual QA

  • NLP QA - End-To-End Memory Networks Implementation (Code)
  • Visual QA - Exploring Models and Data for Image Question Answering Implementation (Code)
  • Visual QA - Exploring Models and Data for Image Question Answering Implementation using tf.nn.dynamic_rnn 😄 (Code)

Week5 - Image Captioning

  • Image Captioning - Show and Tell: A Neural Image Caption Generator Implementation (Code)

Week6 - Neural Style Transfer & TensorBoard

  • Neural Style Transfer - A neural algorithm of artistic style Implementation (Code)
  • Linear Regression with TensorBoard (Code)
  • MNIST Classification with summaries for TensorBoard (Code)

Week7 - Generative Model - Variational AutoEncoder(VAE) & Generative Adversarial Networks(GAN)

  • Variational AutoEncoder(VAE) Implementation (Code)
  • Generative Adversarial Networks(GAN) Implementation (Code)
  • MNIST Data Generation using Generative Adversarial Networks(GAN) 😄 (Code)

Week8 - Autopilot

  • Autopilot - Learning a Driving Simulator Implementation (Code)

Week9 - Semantic Image Segmentation

  • Semantic Image Segmentation - Fully Convolutional Networks for Semantic Segmentation Implementation (Code)

Week10 - Brain Tumor Segmentation & Object Detection & Reinforcement Learning)

  • BRATS Data Example (Code)
  • Brain Tumor Segmentation - Fully Convolutional Networks for Semantic Segmentation Implementation for BRATS Dataset (Code)
  • Object Detection - You Only Look Once: Unified, Real-Time Object Detection Implementation (Code)
  • Object Detection (Code)
  • Reinforcement Learning - DQN - Simple Catch Game (Code)

Appendix

References

[1] https://www.tensorflow.org/

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