计算机科学
人工智能
高光谱成像
支持向量机
模式识别(心理学)
机器学习
人工神经网络
特征选择
深度学习
上下文图像分类
分类器(UML)
遥感
数据挖掘
极限学习机
卷积神经网络
多层感知器
随机森林
作者
Shrutika S. Sawant,Prabukumar Manoharan,Agilandeeswari Loganathan
标识
DOI:10.1007/s12517-021-06984-w
摘要
As the hyperspectral image consists of hundreds of highly correlated spectral bands, the selection of informative and highly discriminative bands is necessary for hyperspectral image classification. The recent growth of machine learning and artificial intelligence techniques play a major role in various domains of hyperspectral image processing. In this paper, a comprehensive survey of machine learning and artificial intelligence technique-based band selection strategies for hyperspectral image classification is given. As per the outcome of this study, we have identified the research challenges and research for future directions in band selection strategies for hyperspectral image classification.
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