Code for our ICASSP 2021 paper: SA-Net: Shuffle Attention for Deep Convolutional Neural Networks

Last update: Jan 08, 2023

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Deep Learning SA-Net

Overview

SA-Net: Shuffle Attention for Deep Convolutional Neural Networks _(paper)

By Qing-Long Zhang and Yu-Bin Yang

[State Key Laboratory for Novel Software Technology at Nanjing University]

Approach

Figure 1: The Diagram of a shuffle attention module.

Owner

Qing-Long Zhang

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Code for our ICASSP 2021 paper: SA-Net: Shuffle Attention for Deep Convolutional Neural Networks

Related tags

Overview

SA-Net: Shuffle Attention for Deep Convolutional Neural Networks _(paper)

Approach

Owner

Qing-Long Zhang

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Code for our ICASSP 2021 paper: SA-Net: Shuffle Attention for Deep Convolutional Neural Networks

Related tags

Overview

SA-Net: Shuffle Attention for Deep Convolutional Neural Networks (paper)

Approach

Owner

Qing-Long Zhang

Using python and scikit-learn to make stock predictions

Official Implementation for the "An Empirical Investigation of 3D Anomaly Detection and Segmentation" paper.

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A Strong Baseline for Image Semantic Segmentation

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The implementation of FOLD-R++ algorithm

Convex optimization for fun and profit.

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Unofficial pytorch implementation of 'Image Inpainting for Irregular Holes Using Partial Convolutions'

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SA-Net: Shuffle Attention for Deep Convolutional Neural Networks _(paper)