Convolutional neural networks (CNNs) have demonstrated impressive performance and have been broadly applied in hyperspectral image (HSI) classification.
Jan 10, 2023 · To resolve the two preceding issues, this article proposes a multiscale cross interaction attention network (MCIANet) for HSI classification.
Recently, hyperspectral image (HSI) classification methods based on deep-learning have attracted widespread attention. Convolutional neural networks, as a ...
Title: A Multiscale Cross Interaction Attention Network for Hyperspectral Image Classification. Language: English; Authors: Liu, Dongxu1,2 (AUTHOR)
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Recently, hyperspectral image (HSI) classification methods based on convolutional neural networks (CNN) have shown impressive performance.
Jun 17, 2022 · This module pays more attention to the significant channels and suppresses the redundant channels. Finally, the residual connection is used to ...
ECA is a lightweight and local cross-channel feature interaction attention model without dimensionality reduction [45]. ... Attention Network for Hyperspectral ...
Article "A Multiscale Cross Interaction Attention Network for Hyperspectral Image Classification" Detailed information of the J-GLOBAL is an information ...
Multiscale Convolutional Neural Networks (CNNs) are effective in feature extraction for HSI classification by considering different scales in the image data.
Missing: Interaction | Show results with:Interaction
May 3, 2024 · Hyperspectral and Multi-source Heterogeneous Data Fusion Classification Based on Multiscale Multi-source Interaction Attention Network.