Dxtcpserver
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Semantic Segmentation Suite | 2,311 | 3 years ago | 83 | Python | ||||||
| Semantic Segmentation Suite in TensorFlow. Implement, train, and test new Semantic Segmentation models easily! | ||||||||||
| Lednet | 425 | 3 years ago | 9 | mit | Python | |||||
| LEDNet: A Lightweight Encoder-Decoder Network for Real-time Semantic Segmentation | ||||||||||
| Tensorflow Multigpu Vae Gan | 399 | 5 years ago | 10 | mit | Jupyter Notebook | |||||
| A single jupyter notebook multi gpu VAE-GAN example with latent space algebra and receptive field visualizations. | ||||||||||
| Began | 198 | 3 years ago | 5 | mit | Python | |||||
| Boundary Equibilibrium Generative Adversarial Networks Implementation in Tensorflow | ||||||||||
| Seq2seqsharp | 188 |  | 3 | 3 months ago | 1 | May 09, 2022 | 6 | other | C# | |
| Seq2SeqSharp is a tensor based fast & flexible deep neural network framework written by .NET (C#). It has many highlighted features, such as automatic differentiation, different network types (Transformer, LSTM, BiLSTM and so on), multi-GPUs supported, cross-platforms (Windows, Linux, x86, x64, ARM), multimodal model for text and images and so on. | ||||||||||
| Review_net | 180 | 6 years ago | 3 | mit | Lua | |||||
| Review Network for Caption Generation | ||||||||||
| Alphastar_implementation | 168 | 3 months ago | 1 | apache-2.0 | Python | |||||
| This project is implementation code of AlphaStar | ||||||||||
| Linknet | 150 | 7 years ago | 4 | Lua | ||||||
| Saliency | 140 | a year ago | 3 | mit | Python | |||||
| Contextual Encoder-Decoder Network for Visual Saliency Prediction [Neural Networks 2020] | ||||||||||
| Gon | 123 | 3 years ago | mit | Python | ||||||
| Gradient Origin Networks - a new type of generative model that is able to quickly learn a latent representation without an encoder | ||||||||||
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