Titlebook: Hyperspectral Image Analysis; Advances in Machine Saurabh Prasad,Jocelyn Chanussot Book 2020 Springer Nature Switzerland AG 2020 Hyperspec

recede

Saurabh Prasad,Jocelyn ChanussotProvides a comprehensive review of the state of the art in hyperspectral image analysis.Presents perspectives from experts who are pioneers in a broad range of signal processing and machine learning f

Antagonist

同步信息

https://doi.org/10.1007/978-3-030-38617-7Hyperspectral Image Analysis; Manifold Learning; Subspace Learning; Computational Imaging; Target Recogn

Arboreal

Machine Learning Methods for Spatial and Temporal Parameter Estimation,d from time series of vegetation optical depth; and finally (3) we show the combination of radiative transfer models with random forests to estimate leaf area index, fraction of absorbed photosynthetically active radiation, fraction vegetation cover, and canopy water content at global scale from lon

fidelity

HAVOC

没有准备

Multiple Kernel Learning for Hyperspectral Image Classification,the nonlinear MKL, the sparse MKL, and the ensemble MKL. The goal of this chapter is to provide a systematic review of MKL methods, which have been applied to HSI classification. We also analyze and evaluate different MKL algorithms and their respective characteristics in different cases of HSI clas

AROMA

享乐主义者

uncertain