https://github.com/m0hc3n/deep-neural-networks-architectures-for-computer-vision-tasks

This repository bundles the implementation of some well-known Deep Neural Networks Architectures made for Computer Vision Task using Pytorch (why pytorch ? cuz Tensorflow is for boomers ! duh...).
https://github.com/m0hc3n/deep-neural-networks-architectures-for-computer-vision-tasks

computer-vision deep-learning gan inception resnet

Last synced: 3 months ago
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This repository bundles the implementation of some well-known Deep Neural Networks Architectures made for Computer Vision Task using Pytorch (why pytorch ? cuz Tensorflow is for boomers ! duh...).

• Host: GitHub
• URL: https://github.com/m0hc3n/deep-neural-networks-architectures-for-computer-vision-tasks
• Owner: M0hc3n
• Created: 2024-08-06T15:38:15.000Z (6 months ago)
• Default Branch: master
• Last Pushed: 2024-10-13T20:17:58.000Z (4 months ago)
• Last Synced: 2024-10-20T13:23:07.672Z (3 months ago)
• Topics: computer-vision, deep-learning, gan, inception, resnet
• Language: Python
• Homepage:
• Size: 68.2 MB
• Stars: 4
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
## Deep-Neural-Networks-Architectures-For-Computer-Vision-Tasks

This repository bundles the implementation of some well-known Deep Neural Networks Architectures made for Computer Vision Task using Pytorch (why pytorch ? cuz Tensorflow is for boomers ! duh...).

In each folder, you will find the implmentation of the corresponding architecture, and a set of resources (articles, papers, videos...) that helped to understand the discussed architecture. If you want to understand the general folder structure, then head to ``/Deep Neural Networks``, where you will find a generic DNN implementation along with descriptions for each folder and file.

I'll be working more on this repository in the upcoming time, as I have some architectures (and improvements) in mind to do. I'll try to summarize them here:

- [x] Deep Neural Network

- [ ] Genrative Adversarial Networks (GANs)

  - [x] Deep Convolutional Genrative Adversarial Networks (DCGAN)

  - [x] Conditional Genrative Adversarial Networks (cGAN)

  - [X] Cycle Genrative Adversarial Networks (CycleGAN)

  - [X] Bicycle Genrative Adversarial Networks (BicycleGAN)

- [x] Residual Networks

- [ ] GoogleLeNet (Inception)

  - [x] Inception v1

  - [ ] Inception v2

  - [ ] Inception v3

  - [ ] Inception v4

  - [ ] Inception-ReNet

- [ ] YOLO (You Only Look Once)

  - [X] YOLO V1

  - [ ] YOLO V2

  - [ ] YOLO V3

  

A huge thanks for Rohan Paul, and his Youtube series (which you find its code base [here](https://github.com/rohan-paul/MachineLearning-DeepLearning-Code-for-my-YouTube-Channel/tree/master)) for being a motivator of this repository. He had also helped a lot with understanding the original research papers and implementing those architectures.