Heqing Huang
An Incremental SAR Target Recognition Framework via Memory-Augmented Weight Alignment and Enhancement Discrimination
Huang, Heqing; Gao, Fei; Wang, Jun; Hussain, Amir; Zhou, Huiyu
Abstract
Synthetic aperture radar automatic target recognition (SAR ATR) is one of the most important research directions in SAR image interpretation. While much existing research into SAR ATR has focused on deep learning technology, an equally important yet underexplored problem is its deployment in incremental learning (IL) scenarios. This letter proposes a new benchmark approach, termed memory augmented weights alignment and enhancement discrimination IL (MEDIL) algorithm to address this issue. First, the attention mechanism is employed as part of the benchmark. Next, we discuss the problem of height deviation of weights at the fully connected layer and design a more suitable alignment of weights by guiding the memory module for contextual data processing. In addition, we leverage the incremental progressive sampling strategy to alleviate the imbalance between old and new classes during the training period. Finally, we propose to enhance the distinction among various classes with an angular penalty loss function to ensure the diversity of incremental instances. The proposed method is evaluated on moving and stationary target acquisition and recognition (MSTAR) and OpenSARShip under different experimental settings. Experimental results demonstrate that our proposed approach can effectively solve catastrophic forgetting in SAR multiclass recognition problems.
Citation
Huang, H., Gao, F., Wang, J., Hussain, A., & Zhou, H. (2023). An Incremental SAR Target Recognition Framework via Memory-Augmented Weight Alignment and Enhancement Discrimination. IEEE Geoscience and Remote Sensing Letters, 20, https://doi.org/10.1109/lgrs.2023.3269480
Journal Article Type | Article |
---|---|
Online Publication Date | Apr 24, 2023 |
Publication Date | 2023 |
Deposit Date | Jun 28, 2023 |
Publicly Available Date | Jul 24, 2023 |
Journal | IEEE Geoscience and Remote Sensing Letters |
Print ISSN | 1545-598X |
Electronic ISSN | 1558-0571 |
Publisher | Institute of Electrical and Electronics Engineers |
Peer Reviewed | Peer Reviewed |
Volume | 20 |
DOI | https://doi.org/10.1109/lgrs.2023.3269480 |
Files
An Incremental SAR Target Recognition Framework via Memory-Augmented Weight Alignment and Enhancement Discrimination (accepted version)
(584 Kb)
PDF
You might also like
MTFDN: An image copy‐move forgery detection method based on multi‐task learning
(2024)
Journal Article
Transition-aware human activity recognition using an ensemble deep learning framework
(2024)
Journal Article
Downloadable Citations
About Edinburgh Napier Research Repository
Administrator e-mail: repository@napier.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2024
Advanced Search