@inproceedings{f44ba42b5afb43dd8ccafdc81f74d932,
title = "SPTF-YOLO: A Sonar-Parameter-Embedded and Time-Frequency-Feature-Guided YOLO for Object Detection in Sonar Images",
abstract = "Sonar image detection faces challenges from noise, low resolution, and limited annotated data. We propose a Sonar-Parameter-Embedded and Time{\textendash}Frequency-Feature-Guided YOLO (SPTF-YOLO), which integrates sonar-specific priors and time{\textendash}frequency features via a prior knowledge branch. Experiments on the underwater acoustic target detection (UATD) sub-dataset show that SPTF-YOLO outperforms YOLOX and YOLOv8, achieving higher mean average precision (mAP).",
keywords = "Object detection, Sonar images, YOLO, underwater target detection",
author = "Xiaoguang Chen and Wei Li and Fanyang Meng and Lin Mei",
note = "Publisher Copyright: {\textcopyright} 2025 Copyright held by the owner/author(s); 19th International Conference on Underwater Networks and Systems, WUWNet 2025 ; Conference date: 29-10-2025 Through 31-10-2025",
year = "2026",
month = may,
day = "22",
doi = "10.1145/3784941.3785432",
language = "英语",
series = "WUWNet 2025 - The 19th International Conference on Underwater Networks and Systems",
publisher = "Association for Computing Machinery, Inc",
booktitle = "WUWNet 2025 - The 19th International Conference on Underwater Networks and Systems",
}