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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Google MobileNet implementation with Keras
| Date | Stars |
|---|---|
| 2026-07-24 | 258 |
| 2026-07-25 | 258 |
| 2026-07-28 | 258 |
| 2026-07-30 | 258 |
| 2026-08-06 | 258 |
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growth rate 0.00%/day
## Note: This project is not maintained anymore. Mobilenet implementation is already included in Keras Applications folder. [Mobilenet](https://github.com/fchollet/keras/blob/master/keras/applications/mobilenet.py) # Keras MobileNet Google MobileNet Implementation using Keras Framework 2.0 ### Project Summary - This project is just the implementation of paper from scratch. I don't have the pretrained weights or GPU's to train :) - Separable Convolution is already implemented in both Keras and TF but, there is no BN support after Depthwise layers (Still investigating). - Custom Depthwise Layer is just implemented by changing the source code of Separable Convolution from Keras. [Keras: Separable Convolution](https://github.com/fchollet/keras/blob/master/keras/layers/convolutional.py#L806) - There is probably a typo in Table 1 at the last "Conv dw" layer stride should be 1 according to input sizes. - Couldn't find any information about the usage of biases at layers (not used as default). ### TODO - [x] Add Custom Depthwise Convolution - [x] Add BN + RELU layers - [x] Check layer shapes - [ ] Test Custom Depthwise Convolution - [ ] Benchmark training and feedforward pass with both CPU and GPU - [ ] Compare with [SqueezeNet](https://github.com/rcmalli/keras-squeezenet) ### Library Versions - Keras v2.0+ - Tensorflow 1.0+ (not supporting Theano for now) ### References 1) [Keras Framework](www.keras.io) 2) [Google MobileNet Paper](https://arxiv.org/pdf/1704.04861.pdf) ### Licence MIT License Note: If you find this project useful, please include reference link in your work.
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Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:c29a24ba4265768b, topic:tensorflow