Nov 4, 2020 · It allows the separation of spectral and spatial information in HSI and also greatly reduces the network size to prevent the overfitting issue.

The experiment results demonstrate that the proposed ResNet compares favorably with several popular deep learning HSI classifiers and that the ResNet-CRF ...

Abstract—To build small and efficient neural networks for hyperspectral image (HSI) classification, this letter presents a depthwise separable residual ...

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Oct 22, 2024 · A Depthwise Separable Fully Convolutional ResNet with Region Growing for Semi-supervised Hyperspectral Image Classification. April 2021; IEEE ...

A hyperspectral image classification method based on deep separable residual attention network is proposed to address the above issues.

To build small and efficient neural networks for hyperspectral image (HSI) classification, this letter presents a depthwise separable residual neural network ( ...

This paper proposes a modified depthwise separable relational network to deeply capture the similarity between samples.

A Multi-Scale Depthwise Separable Capsule Network (MDSC-Net) is proposed in this article for HSI classification.

A Depthwise Separable Fully Convolutional ResNet ... Objective Evaluation-based High-efficiency Learning Framework for Hyperspectral Image Classification.