MLM-LSTM: multi-layer memory learning framework based on LSTM for hyperspectral change detection.

Li, Yinhe; Yan, Yijun; Ren, Jinchang; Liu, Qiaoyuan; Sun, Haijiang

Abstract

Hyperspectral change detection plays a critical role in remote sensing by leveraging spectral and spatial information for accurate land cover variation identification. Long short-term memory (LSTM) has demonstrated its effectiveness in capturing dependencies and handling long sequences in hyperspectral data. Building on these strengths, a multilayer memory learning model based on LSTM for hyperspectral change detection is proposed, called MLM-LSTM for hyperspectral change detection is proposed. It incorporates shallow memory learning and deep memory learning. The deep memory learning module performs deep feature extraction of long-term and short-term memory separately. Then fully connected layers will be used to fuse the features followed by binary classification for change detection. Notably, our model has higher detection accuracy compared to other state-of-the-art deep learning-based models. Through comprehensive experiments on publicly available datasets, we have successfully validated the effectiveness and efficiency of the proposed MLM-LSTM approach.

Citation

LI, Y., YAN, Y. and REN, C., LIU, Q. and SUN, H. 2024. MLM-LSTM: multi-layer memory learning framework based on LSTM for hyperspectral change detection. In Ren, J., Hussain, A., Liao, I.Y. et al. (eds.) Advances in brain inspired cognitive systems: proceedings of the 13th International conference on Brain-inspired cognitive systems 2023 (BICS 2023), 5-6 August 2023, Kuala Lumpur, Malaysia. Lecture notes in computer sciences, 14374. Cham: Springer [online], pages 51-61. Available from: https://doi.org/10.1007/978-981-97-1417-9_5.

• Presentation Conference Type: Conference Paper (published)
• Conference Name: 13th International conference on Brain-inspired cognitive systems 2023 (BICS 2023)
• Start Date: Aug 5, 2023
• End Date: Aug 6, 2023
• Acceptance Date: Jul 28, 2023
• Online Publication Date: May 22, 2024
• Publication Date: Dec 31, 2024
• Deposit Date: Jun 13, 2024
• Publicly Available Date: May 23, 2025
• Publisher: Springer
• Peer Reviewed: Peer Reviewed
• Pages: 51-61
• Series Title: Lecture notes in computer science (LNCS)
• Series Number: 14374
• Series ISSN: 0302-9743; 1611-3349
• Book Title: Advances in brain inspired cognitive systems
• ISBN: 9789819714162
• DOI: https://doi.org/10.1007/978-981-97-1417-9_5
• Keywords: Hyperspectral image; Change detection; Long short-term memory
• Public URL: https://rgu-repository.worktribe.com/output/2372838