Getsetgo_keras Beginner
Pretrained Convolutional Neural Network models(CNN) (Imagenet challange ILSVRC) are used to predict input image .Codes to extract specific layers ,fine tune and visualize those models are also provided.
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Classification_models | 706 |  | 8 | 4 | 4 years ago | 6 | October 04, 2019 | 11 | mit | Python |
| Classification models trained on ImageNet. Keras. | ||||||||||
| Pytorch Cnn Finetune | 580 |  | 3 | 1 | 4 years ago | 16 | August 05, 2019 | 3 | mit | Python |
| Fine-tune pretrained Convolutional Neural Networks with PyTorch | ||||||||||
| Cnn Models | 348 | 6 years ago | 8 | bsd-2-clause | Python | |||||
| ImageNet pre-trained models with batch normalization for the Caffe framework | ||||||||||
| Glasses | 311 | 2 years ago | 5 | January 25, 2021 | 31 | mit | Jupyter Notebook | |||
| High-quality Neural Networks for Computer Vision 😎 | ||||||||||
| Flaxmodels | 201 |  | 2 | 8 months ago | 4 | August 11, 2023 | 2 | Python | ||
| Pretrained deep learning models for Jax/Flax: StyleGAN2, GPT2, VGG, ResNet, etc. | ||||||||||
| Pretrained | 129 | 2 years ago | 2 | |||||||
| Pretrained is the most complete and frequently updated list of pretrained top-performing models. Tensorflow, Theano and others. Want to add your model? File an issue, and we will add it. | ||||||||||
| Imagenet | 97 | 7 years ago | bsd-3-clause | Python | ||||||
| Pytorch Imagenet Models Example + Transfer Learning (and fine-tuning) | ||||||||||
| Convnetcs | 9 | 6 years ago | C# | |||||||
| convolution neural network library in C# with Pretrained models based on convnetjs | ||||||||||
| Getsetgo_keras Beginner | 5 | 5 years ago | Jupyter Notebook | |||||||
| Pretrained Convolutional Neural Network models(CNN) (Imagenet challange ILSVRC) are used to predict input image .Codes to extract specific layers ,fine tune and visualize those models are also provided. | ||||||||||
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