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implus/SKNet

0
View on GitHub↗
0 stars·0 forks·11 views

SKNet

Features

  • Attention Mechanisms - Selective kernel networks for adaptive receptive field sizes.
  • Image Classification Architectures - Selective kernel network architecture.

Star history

Star history chart for implus/sknetStar history chart for implus/sknet

How this analysis was created: This summary and feature list were written by an AI model that read the project's README and public documentation pages. Each feature links to the documentation it came from; stars, license and language come straight from the GitHub API. The model does not read the source code, and the analysis is refreshed when the project is re-analysed. Learn more on our About page.

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Frequently asked questions

What are the main features of implus/sknet?

The main features of implus/sknet are: Attention Mechanisms, Image Classification Architectures.

What are some open-source alternatives to implus/sknet?

Open-source alternatives to implus/sknet include: 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).

Open-source alternatives to SKNet

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