Implementation of recent Deep Learning papers
Principalele funcționalități ale tdeboissiere/deeplearningimplementations sunt: Computer Vision Models, Deep Learning Models.
Alternativele open-source pentru tdeboissiere/deeplearningimplementations includ: elliottd/groundedtranslation — #GroundedTranslation. jocicmarko/ultrasound-nerve-segmentation — This tutorial shows how to use Keras library to build deep neural network for ultrasound image nerve segmentation.… divamgupta/image-segmentation-keras — Implementation of various Deep Image Segmentation models in keras. lazyprogrammer/machine_learning_examples — This project is a comprehensive collection of practical code examples and implementation libraries for machine… deep-learning-with-pytorch/dlwpt-code — This project is a deep learning educational resource consisting of PyTorch model implementations and code examples. It… openvinotoolkit/open_model_zoo — Open Model Zoo is a curated collection of pre-trained and optimized deep learning models designed for high-performance…
This tutorial shows how to use Keras library to build deep neural network for ultrasound image nerve segmentation. More info on this Kaggle competition can be found on https://www.kaggle.com/c/ultrasound-nerve-segmentation.
Implementation of various Deep Image Segmentation models in keras.
This project is a deep learning educational resource consisting of PyTorch model implementations and code examples. It provides functional Python scripts and notebooks for building, training, and optimizing neural networks using tensor-based computation. The repository includes implementations for designing custom network layers and loss functions, as well as examples of transfer learning workflows that load pretrained model weights to accelerate development. The codebase covers a broad range of deep learning capabilities, including neural network training, custom model component design, and
