Jul 17, 2018 · This paper presents a matrix-based margin-maximization method of band selection with data-driven diversity. In particular, the matrices composed ...
This paper presents a matrix-based margin-maximization method of band selection with data-driven diversity. In particular, the matrices composed of adjacent ...
Abstract— For hyperspectral image classification, high- dimensional spectral features not only increase the computa- tional and storage burden but also ...
A comparative analysis of band selection techniques for hyperspectral image classification � Fruit fly optimization algorithm based on a novel fluctuation model�...
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Matrix-based margin-maximization band selection with data-driven diversity for hyperspectral image classification. X Wei, W Zhu, B Liao, L Cai. IEEE ...
Aug 31, 2020 · This paper presents a spatial spectral mutual information (SSMI) BS scheme that utilizes a spatial feature extraction technique as a preprocessing step.
Matrix-Based Margin-Maximization Band Selection With Data-Driven Diversity for Hyperspectral Image Classification, GeoRS(56), No. 12, December 2018, pp ...
A comparative analysis of band selection techniques for hyperspectral image classification. https://doi.org/10.1109/ic4me247184.2019.9036587.
Matrix-Based Margin-Maximization Band Selection With Data-Driven Diversity for Hyperspectral Image Classification · Xiaohui WeiWen ZhuBo LiaoLijun Cai.
Matrix-Based Margin-Maximization Band Selection With Data-Driven Diversity for Hyperspectral Image Classification. Article. Jul 2018; IEEE T GEOSCI REMOTE.