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Aug 2026

TRIDEN-YOLO: a reparameterized interactive network for underwater object detection

TRIDEN-YOLO, a lightweight detector built upon YOLOv11n, provides the primary reparameterized contextual representation design through multi-branch training and inference-time fusion, while HFFE and GCD loss are incorporated to enhance hierarchical feature fusion and boundary-aware localization.

Xi Chen, Yuping Sun, Kaibin Zeng · 0 citations
Open access Aug 2026

HFQI-YOLO: a lightweight and efficient underwater object detection algorithm

Underwater object detection plays a crucial role in fisheries resource assessment and ecological environment protection. Current underwater object detection models are characterized by large parameter sizes and high computational costs, which hinder the simultaneous achievement of lightweight deployment and high detect...

Xue-Feng Zhao, Yong-Jie Guo, Zhao-Man Zhong et al. · 0 citations
Open access Aug 2026

Performance evaluation of YOLO models for target detection from ocean sidescan sonar imagery

Sidescan sonar images suffer from strong seabed clutter, low gray contrast of underwater targets and frequent missed small targets. Current detection models struggle to balance detection accuracy, inference speed and embedded deployment. To solve these problems, this paper selects six mainstream one-stage detection mod...

Dandan Liu, Hao Chen, Jiajie Chen et al. · 0 citations
Sep 2026

YOLO-PRA: a multi-scale feature fusion and adaptive optimization network for underwater seahorse health detection

Curled-tail posture is an important visual cue for identifying seahorses affected by bacterial enteritis from underwater images in seahorse aquaculture. Therefore, accurate recognition of tail posture is essential for underwater seahorse health detection. However, research on this task is limited by the lack of task-sp...

Bo-Wen Ma, Yang Li, Xian-Jun Fu et al. · 0 citations
Open access Sep 2026

UFL-YOLO: enhancing underwater object detection with lightweight feature refinement and noise-aware loss

Underwater object detection is challenged by visual degradation such as low contrast, background noise and the difficulty of identifying small targets. To alleviate these issues, we propose UFL-YOLO, an enhanced version of YOLOv10 augmented with lightweight yet effective modules: small object enhance pyramid (SOEP), un...

Yu-Xin Wu, Yan Wang, Jing Zhang et al. · 0 citations

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