Principalele funcționalități ale implus/sknet sunt: Attention Mechanisms, Image Classification Architectures.
Alternativele open-source pentru implus/sknet includ: hujie-frank/senet — Squeeze-and-Excitation Networks. jongchan/attention-module — Official PyTorch code for "BAM: Bottleneck Attention Module (BMVC2018)" and "CBAM: Convolutional Block Attention… wang-xinyu/tensorrtx — tensorrtx is a computer vision inference engine and model implementation library designed for graphics processor… fchollet/deep-learning-models — This project is a collection of deep learning tools for image classification and audio tagging, providing a repository… aqibsaeed/genetic-cnn — CNN architecture exploration using Genetic Algorithm. andrew-qibin/coordattention — This repository is a PyTorch implementation of our coordinate attention (will appear in CVPR2021).
Official PyTorch code for "BAM: Bottleneck Attention Module (BMVC2018)" and "CBAM: Convolutional Block Attention Module (ECCV2018)"
This project is a collection of deep learning tools for image classification and audio tagging, providing a repository of pre-trained model weights and architectures. It serves as a Keras model zoo that enables the immediate use of established neural networks for inference and transfer learning. The library includes a music tagging framework that classifies audio recordings using convolutional recurrent neural networks and mel-spectrograms. For visual data, it provides implementations of architectures such as ResNet, VGG, and Xception, alongside a repository of weights trained on large datase
tensorrtx is a computer vision inference engine and model implementation library designed for graphics processor acceleration. It provides a framework for optimizing deep learning models through a GPU inference optimizer, a deep learning model converter for transforming weights from frameworks like TensorFlow and PyTorch, and a custom plugin library to implement operations not natively supported by the TensorRT API. The project distinguishes itself through a comprehensive collection of pre-defined network implementations, ranging from various YOLO versions and DETR transformers for object det
