2024
DOI: 10.1109/jstars.2024.3404607
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Tucker Decomposition-Based Network Compression for Anomaly Detection With Large-Scale Hyperspectral Images

Yulei Wang,
Hongzhou Wang,
Enyu Zhao
et al.

Abstract: Deep learning methodologies have demonstrated considerable effectiveness in hyperspectral anomaly detection (HAD). However, the practicality of deep learning-based HAD in real-world applications is impeded by challenges arising from limited labeled data, large-scale hyperspectral images and constrained computational resources. In light of these challenges, this paper introduces a convolutional neural network-based HAD model through the incorporation of Tucker decomposition, named as TD-CNND. Drawing inspiratio… Show more

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