hoanglechau/channelwise-attention-residual-networks-dl

This project implements a Squeeze-and-Excitation Residual Network (SE-ResNet) to solve a fine-grained classification problem on 32 × 32 images. It addresses signal-to-noise challenges in low-resolution data.

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Experimental
No License No Package No Dependents
Maintenance 10 / 25
Adoption 0 / 25
Maturity 3 / 25
Community 0 / 25

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cifar-10-image-classification

Last pushed

Jan 28, 2026

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CIFAR 10 Image Classification · 111 frameworks

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