LF-CNN:深度学习引导的遥感分类小样本目标检测

IF 2.2 4区工程技术 Q2 ENGINEERING, MULTIDISCIPLINARY

Cmes-computer Modeling in Engineering & Sciences Pub Date : 2022-01-01 DOI:10.32604/cmes.2022.019202

Chengfan Li, Lan Liu, Junjuan Zhao, Xuefeng Liu

引用次数: 7

摘要

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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LF-CNN: Deep Learning-Guided Small Sample Target Detection for Remote Sensing Classification

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来源期刊

Cmes-computer Modeling in Engineering & Sciences ENGINEERING, MULTIDISCIPLINARY-MATHEMATICS, INTERDISCIPLINARY APPLICATIONS

CiteScore

3.80

自引率

16.70%

发文量

298

审稿时长

7.8 months

期刊介绍： This journal publishes original research papers of reasonable permanent value, in the areas of computational mechanics, computational physics, computational chemistry, and computational biology, pertinent to solids, fluids, gases, biomaterials, and other continua. Various length scales (quantum, nano, micro, meso, and macro), and various time scales ( picoseconds to hours) are of interest. Papers which deal with multi-physics problems, as well as those which deal with the interfaces of mechanics, chemistry, and biology, are particularly encouraged. New computational approaches, and more efficient algorithms, which eventually make near-real-time computations possible, are welcome. Original papers dealing with new methods such as meshless methods, and mesh-reduction methods are sought.