Spectral-Spatial Active Learning With Structure Density for Hyperspectral Classification

Spectral-Spatial Active Learning With Structure Density for Hyperspectral Classification

In this paper, a spectral-spatial active learning (AL) method is proposed based on an up-to-date unlabeled samples sampling strategy concentrated on the structure density supported by breaking ties. The proposed sampling criterion in AL is used for hyperspectral image classification, which involves...

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Bibliographic Details
Main Authors: Qianming Li, Bohong Zheng, Yusheng Yang
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Hyperspectral imagery
active learning
structure density
breaking ties
sampling criterion
Online Access:https://ieeexplore.ieee.org/document/9409072/

Internet

https://ieeexplore.ieee.org/document/9409072/

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