Application Tutorial of Deep Learning in Image Processing

Foreword

This tutorial is to organize and summarize the research content of my postgraduate period. At the same time, I hope to help more friends. If there is any new knowledge learned later, I will share it with you.。
This tutorial will be shared in the form of video, the teaching process is as follows：

1）Introduce the structure and innovation of the network
2）Use Pytorch for network construction and training 3）3) Use Tensorflow (internal keras module) to build and train the network

All PPTs in the course are placed in the course_ppt folder, and you need to download them yourself。

Tutorial directory, click to jump to the corresponding video (it will be added later according to the learning content)

Image Classification
- LeNet（COMPLETED）
  - Pytorch official demo (Lenet)
  - Tensorflow2 official demo
- AlexNet（已完成）
- VggNet（已完成）
- GoogLeNet（已完成）
- ResNet（已完成）
- ResNeXt (已完成)
  - ResNeXt网络讲解
  - Pytorch搭建ResNeXt网络
- MobileNet_v1_v2（已完成）
- MobileNet_v3（已完成）
- ShuffleNet_v1_v2 (已完成)
- EfficientNet_v1（已完成）
- EfficientNet_v2 (已完成)
- Vision Transformer(已完成)
- Swin Transformer(已完成)
- ConvNeXt(准备中)
  - ConvNeXt网络讲解
  - 使用Pytorch搭建ConvNeXt
目标检测
- Faster-RCNN/FPN（已完成）
- SSD/RetinaNet (已完成)
- YOLOv3 SPP (已完成)
  - YOLO系列网络讲解
  - YOLOv3 SPP源码解析(Pytorch版)
语义分割
- FCN (已完成)
  - FCN网络讲解
  - FCN源码解析(Pytorch版)
- DeepLabV3 (已完成)
- LR-ASPP (已完成)
  - LR-ASPP网络讲解
  - LR-ASPP源码解析(Pytorch版)
- U-Net (已完成)
  - U-Net网络讲解
  - U-Net源码解析(Pytorch版)

更多相关视频请进入我的bilibili频道查看

所需环境

Anaconda3（建议使用）
python3.6/3.7/3.8
pycharm (IDE)
pytorch 1.7.1 (pip package)
torchvision 0.8.1 (pip package)
tensorflow 2.4.1 (pip package)

欢迎大家关注下我的微信公众号（阿喆学习小记），平时会总结些相关学习博文。

如果有什么问题，也可以到我的CSDN中一起讨论。 https://blog.csdn.net/qq_37541097/article/details/103482003

我的bilibili频道： https://space.bilibili.com/18161609/channel/index

About

deep learning for image processing including classification and object-detection etc.

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