TL;DR
The proposed UW-D-FINE, an enhanced real-time detector addressing underwater object detection challenges through three key innovations, enhances the backbone by integrating parallel multi-scale convolutional branches with omnidirectional depthwise convolutions, enabling more effective extraction of discriminative features from color-degraded images.
Results support the effectiveness of the proposed framework for mixed-scale underwater object detection, including small-scale objects, and compare with the YOLOv11 baseline.
Experimental results demonstrate that the proposed Bidirectional weighted Concat with Efficient multi-scale Attention You Only Look Once (BCEA-YOLO) method outperforms competing methods for underwater object detection, and edge deployment tests on the NVIDIA Jetson platform validate its real-time inference efficiency.
A dynamic image feature fusion backbone module, termed DyC2F (dynamic lightweight convolution to fusion), is developed, which enhances the modeling of local textures and weak boundary features while maintaining low computational complexity.
A global-local feature collaborative underwater image enhancement network that adopts a three-branch collaborative architecture to model local structural details, cross-color channel dependencies, and global contextual information, enabling joint optimization of global consistency and local discriminability is proposed...
A novel underwater target detection framework that integrates feature enhancement with semantic-spatial guided fusion, built upon the RT-DETR architecture, that significantly reduces false positives and missed detections while maintaining real-time performance is proposed.
Underwater object detection techniques for marine resource exploration, underwater engineering inspection, and AUV intelligent operations face three major demands: high precision, low latency, and embeddable deployment. In natural underwater environments, complex interferences such as water scattering, wavelength-selec...
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.
