Unfolding multilevel agglomerative strategies for SVM classification: a case study in discriminating spectrally similar land covers

IF 1.4 4区地球科学 Q3 IMAGING SCIENCE & PHOTOGRAPHIC TECHNOLOGY

Remote Sensing Letters Pub Date : 2024-09-09 DOI:10.1080/2150704x.2024.2398813

Willian Vieira de Oliveira, Luciano Vieira Dutra, Sidnei João Siqueira Sant’Anna

引用次数: 0

Abstract

In remote sensing applications, image classification algorithms normally require parameter optimization strategies to adapt to the complexities of the data and determine the model’s parameters for ...

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为 SVM 分类展开多级聚类策略：光谱相似地表覆盖物判别案例研究

在遥感应用中，图像分类算法通常需要参数优化策略，以适应数据的复杂性，并确定模型的参数，以 ...

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来源期刊

Remote Sensing Letters REMOTE SENSING-IMAGING SCIENCE & PHOTOGRAPHIC TECHNOLOGY

CiteScore

4.10

自引率

4.30%

发文量

审稿时长

6-12 weeks

期刊介绍： Remote Sensing Letters is a peer-reviewed international journal committed to the rapid publication of articles advancing the science and technology of remote sensing as well as its applications. The journal originates from a successful section, of the same name, contained in the International Journal of Remote Sensing from 1983 –2009. Articles may address any aspect of remote sensing of relevance to the journal’s readership, including – but not limited to – developments in sensor technology, advances in image processing and Earth-orientated applications, whether terrestrial, oceanic or atmospheric. Articles should make a positive impact on the subject by either contributing new and original information or through provision of theoretical, methodological or commentary material that acts to strengthen the subject.