Information Leakage in Deep Learning-Based Hyperspectral Image Classification: A Survey

doi:10.3390/rs15153793

CIOMP OpenIR

	Information Leakage in Deep Learning-Based Hyperspectral Image Classification: A Survey
	H. Feng; Y. Wang; Z. Li; N. Zhang; Y. Zhang and Y. Gao
	2023
发表期刊	Remote Sensing
ISSN	20724292
卷号	15 期号:15
摘要	In deep learning-based hyperspectral remote sensing image classification tasks, random sampling strategies are typically used to train model parameters for testing and evaluation. However, this approach leads to strong spatial autocorrelation between the training set samples and the surrounding test set samples, and some unlabeled test set data directly participate in the training of the network. This leaked information makes the model overly optimistic. Models trained under these conditions tend to overfit to a single dataset, which limits the range of practical applications. This paper analyzes the causes and effects of information leakage and summarizes the methods from existing models to mitigate the effects of information leakage. Specifically, this paper states the main issues in this area, where the issue of information leakage is addressed in detail. Second, some algorithms and related models used to mitigate information leakage are categorized, including reducing the number of training samples, using spatially disjoint sampling strategies, few-shot learning, and unsupervised learning. These models and methods are classified according to the sample-related phase and the feature extraction phase. Finally, several representative hyperspectral image classification models experiments are conducted on the common datasets and their effectiveness in mitigating information leakage is analyzed. © 2023 by the authors.
DOI	10.3390/rs15153793
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收录类别	sci ; ei
引用统计
文献类型	期刊论文
条目标识符	http://ir.ciomp.ac.cn/handle/181722/67453
专题	中国科学院长春光学精密机械与物理研究所
推荐引用方式 GB/T 7714	H. Feng,Y. Wang,Z. Li,et al. Information Leakage in Deep Learning-Based Hyperspectral Image Classification: A Survey[J]. Remote Sensing,2023,15(15).
APA	H. Feng,Y. Wang,Z. Li,N. Zhang,&Y. Zhang and Y. Gao.(2023).Information Leakage in Deep Learning-Based Hyperspectral Image Classification: A Survey.Remote Sensing,15(15).
MLA	H. Feng,et al."Information Leakage in Deep Learning-Based Hyperspectral Image Classification: A Survey".Remote Sensing 15.15(2023).

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