Metadata-Version: 2.1
Name: diagtomodel
Version: 0.3.3
Summary: Implementations of Artificial Neural Networks Based on their Diagrams
Home-page: https://github.com/EverLookNeverSee/diag2model
Author: Milad Sadeghi DM
Author-email: EverLookNeverSee@ProtonMail.ch
License: UNKNOWN
Project-URL: GitHub Pages, https://everlookneversee.github.io/diag2model/
Project-URL: Bug Tracker, https://github.com/EverLookNeverSee/diag2model/issues
Keywords: Python,Machine Learning,Computer Vision,Deep Learning,Neural Networks
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE

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### Implementations of Artificial Neural Networks Based on their Diagrams

## Authors
* Milad Sadeghi DM - [EverlookNeverSee@GitHub](https://github.com/EverLookNeverSee)
* List of [all contributors](https://github.com/EverLookNeverSee/diagtomodel/graphs/contributors) to this repository

## Implemented Models
* [PLNet](diagtomodel/pl_net/pl_net.py) - Convolutional Neural Network with Parallel Layers
* [MLANet](diagtomodel/mla_net/mla_net.py) - Convolutional Neural Network with Multiple Layer Additions
* [LeNet-5](diagtomodel/lenet_5/lenet-5.py) - Gradient-Based Learning Applied to Document Recognition
* [AlexNet](diagtomodel/alexnet/alexnet.py) - ImageNet Classification with Deep Convolutional
Neural Networks
* [VGG-16](diagtomodel/vgg_16/vgg-16.py) - Very Deep Convolutional Networks For Large Scale Image Recognition
* [Inception-v1](diagtomodel/inception_v1/inception-v1.py) - Going Deeper With Convolutions
* [Xception](diagtomodel/xception/xception.py) - Deep Learning with Depthwise Separable Convolutions


## License
This project licensed under the MIT License - see the [LICENSE](LICENSE) file for more details.


