FSBNet: A Classifying Framework of Disaster Scene for Volcanic Lithology Through Deep-Learning Models

FSBNet: A Classifying Framework of Disaster Scene for Volcanic Lithology Through Deep-Learning Models

Volcanic lithology classification is one of the fundamental tasks in remote sensing investigation of disaster scenes, and deep learning can improve the accuracy and efficiency of classification. Here, a new focused squeeze-and-excitation (SE) attention and bilinear interpolation network (FSBNet) is...

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Bibliographic Details
Main Authors: Lan Liu, Zhouyi Xiao, Jianpeng Hu, Jingxin Han, Jung Yoon Kim, Rohit Sharma, Chengfan Li
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Changbaishan mountain
deep learning
disaster scene classification
remote sensing image
volcanic lithology
Online Access:https://ieeexplore.ieee.org/document/11030265/
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https://ieeexplore.ieee.org/document/11030265/

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