Jun 6, 2024 · In underwater object detection, a crucial method for marine exploration, the presence of small objects in underwater environments significantly hampers the performance of detection. In this paper, a dynamic YOLO detector is proposed as a …

Apr 24, 2024 · YOLO-UOD, a novel algorithm for target detection systems, is introduced here. Built upon the YOLOv7 framework, it particularly addresses the challenge of detecting targets in underwater environments. The network structure of YOLO-UOD comprises a backbone, neck layers, and detection heads.

Aug 11, 2022 · Through significant non-parametric tests on YOLOv4-tiny, YOLOv5s, YOLOv5m, and YOLO-UOD, the results show that the proposed YOLO-UOD is significantly different from YOLOv4-tiny and YOLO-UOD has improved underwater object detection performance.

Jan 27, 2024 · In this paper, we propose a high-precision, lightweight underwater detector specifically optimizing for underwater scenarios based on the You Only Look Once Version 8 (YOLOv8) model.

Mar 24, 2024 · These results demonstrate that the proposed UOD model can successfully detect targets as small as 5 cm (i.e., cylinder) through transfer learning. This approach shows promise for application in underwater SHM, particularly in detecting apparent damages such as …

Apr 24, 2024 · In terms of loss calculation, the optimized normalized Wasserstein distance approach is used to predict the box distribution probabilistic modelling method to determine comparable distances to the...

Jan 3, 2025 · In order to enhance underwater object perception and improve target detection precision, we propose a lightweight underwater target detection method using You Only Look Once (YOLO) v8 with multi-scale cross-channel attention (MSCCA), named YOLOv8-UOD.

Apr 24, 2024 · Here, we propose a novel convolutional omni‐efficient layer aggregation network structure and an optimized loss calculation function based on Gaussian modelling, and apply effective underwater image enhancement techniques to our detector, achieving better performance than existing detectors. 1. Pang,Y.,Wu,C.,Wu,H.,Yu,X.:

Abstract—Underwater object detection (UOD) is crucial for marine economic development, environmental protection, and the planet’s sustainable development. The main challenges of this task arise from low-contrast, small objects, and mimicry of aquatic organisms. The key to addressing these challenges is to

Mar 9, 2022 · The experimental results show that the proposed UOD approach achieved 47.9 mAP in URPC2017 and 70.3 mAP in URPC2018, outperforming many state-of-the-art UOD methods and indicating the designed method is more suitable for UOD.