Musket
发表于 2025-3-23 09:48:52
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吃掉
发表于 2025-3-23 16:53:07
Recursive Hyperspectral Sample Processing of Maximum Likelihood Estimationxing model (ALMM) that can adapt to the signatures, referred to as virtual signatures (VSs), generated directly from data in an unsupervised and recursive manner. This chapter considers an alternative approach to RHSP-LSMA, called recursive hyperspectral sample processing of maximal likelihood estim
Apraxia
发表于 2025-3-23 21:52:51
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Nuance
发表于 2025-3-24 00:28:14
Recursive Hyperspectral Sample Processing of Geometric Simplex Growing Algorithmonsquare matrix, which involves excessive computing time in calculating the matrix determinant. This type of SV calculation is referred to as a determinant-based SV (DSV) calculation (Chap. .). Therefore, several preprocessing steps are suggested for DSV calculation in Chap. . to ease computational
ACRID
发表于 2025-3-24 03:42:43
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多节
发表于 2025-3-24 08:06:21
Recursive Hyperspectral Band Processing for Passive Target Detection: Anomaly Detectiond anomaly detection, New York, 2016), where the main focus of AD is on the design and development of AD algorithms for causal processing, which is a prerequisite for real-time processing. Chapter . in this book makes use of causality to further develop various real-time processing versions of AD so
ovation
发表于 2025-3-24 12:11:54
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Aerate
发表于 2025-3-24 18:53:19
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使出神
发表于 2025-3-24 22:29:57
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Embolic-Stroke
发表于 2025-3-25 02:20:55
Introduction,003)], removal of highly correlated interband information by data compression or data reduction, data communication, and transmission once hyperspectral imaging sensors are deployed in space. One effective means of dealing with these issues is to develop real-time hyperspectral imaging algorithms th