Year: 2026
Type: article
Abstract: Ocean internal waves (IWs), induced by density stratification and fluid perturbations, are significant oceanic phenomena prevalent across global oceans, profoundly impacting marine environments and engineering safety. Although one-stage object detection models are favored in practical applications due to their efficient inference, they often suffer from insufficient accuracy in IW detection tasks. To address this, we introduce a novel one-stage, anchor-free detection approach based on Transformer for IW detection, proposing a new algorithm named IW-D-FINE, which balances detection accuracy and inference efficiency. On the public SAR dataset, IW-D-FINE achieves an [email protected] of 90.5, significantly outperforming existing one-stage methods while maintaining faster inference speeds than mainstream two-stage models. Furthermore, to mitigate the scarcity of internal wave samples, we construct a small-scale IWs dataset, YH3-IW-2025, and validate the algorithm thoroughly on this dataset. Experimental results demonstrate that IW-D-FINE exhibits robust performance under complex background interference, highlighting its application potential and scalability in IW detection tasks.
DOI: 10.3390/jmse14040388
Authors: Lu Yu, Yanping Tian, Jie Chen, Cheng Chi, Tingting Li, Jianwei Li
Institution: PLA Navy Submarine Academy
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $3,137
OpenAlex ID: W7130518168