|
|
|
|
|
Changhong Liu, Jiawen Wen, Jinshan Huang, Weiren Lin, Bochun Wu, Ning Xie and Tao Zou
Underwater object detection is crucial in marine exploration, presenting a challenging problem in computer vision due to factors like light attenuation, scattering, and background interference. Existing underwater object detection models face challenges ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Jier Xi and Xiufen Ye
There are many challenges in using side-scan sonar (SSS) images to detect objects. The challenge of object detection and recognition in sonar data is greater than in optical images due to the sparsity of detectable targets. The complexity of real-world u...
ver más
|
|
|
|
|
|
|
|
|
|
|
Jiawei Zhang, Fenglei Han, Duanfeng Han, Jianfeng Yang, Wangyuan Zhao and Hansheng Li
In the realm of ocean engineering and maintenance of subsea structures, accurate underwater distance quantification plays a crucial role. However, the precision of such measurements is often compromised in underwater environments due to backward scatteri...
ver más
|
|
|
|
|
|
|
|
|
|
|
Zhuo Wang, Haojie Chen, Hongde Qin and Qin Chen
In the computer vision field, underwater object detection has been a challenging task. Due to the attenuation of light in a medium and the scattering of light by suspended particles in water, underwater optical images often face the problems of color dis...
ver más
|
|
|
|
|
|
|
|
|
|
|
Yutuo Yang, Wei Liang, Daoxian Zhou, Yinlong Zhang and Gaofei Xu
Cultural artifacts found underwater are located in complex environments with poor imaging conditions. In addition, the artifacts themselves present challenges for automated object detection owing to variations in their shape and texture caused by breakag...
ver más
|
|
|
|
|
|
|
|
|
|
|
Jing Wang, Qianqian Li, Zhiqiang Fang, Xianglong Zhou, Zhiwei Tang, Yanling Han and Zhenling Ma
The rapid development of convolutional neural networks has significant implications for automated underwater fishing operations. Among these, object detection algorithms based on underwater robots have become a hot topic in both academic and applied rese...
ver más
|
|
|
|
|
|
|
|
|
|
|
Liang Zhao, Qing Yun, Fucai Yuan, Xu Ren, Junwei Jin and Xianchao Zhu
Underwater target detection plays a crucial role in marine environmental monitoring and early warning systems. It involves utilizing optical images acquired from underwater imaging devices to locate and identify aquatic organisms in challenging environme...
ver más
|
|
|
|
|
|
|
|
|
|
|
Hao Wang and Nanfeng Xiao
In order to better utilize and protect marine organisms, reliable underwater object detection methods need to be developed. Due to various influencing factors from complex and changeable underwater environments, the underwater object detection is full of...
ver más
|
|
|
|
|
|
|
|
|
|
|
Feihu Zhang, Wei Zhang, Chensheng Cheng, Xujia Hou and Chun Cao
Deep learning-based object detection methods have demonstrated remarkable effectiveness across various domains. Recently, there has been growing interest in applying these techniques to underwater environments. Conventional optical imaging methods face s...
ver más
|
|
|
|
|
|
|
|
|
|
|
Xin Yuan, Shutong Fang, Ning Li, Qiansheng Ma, Ziheng Wang, Mingfeng Gao, Pingpeng Tang, Changli Yu, Yihan Wang and José-Fernán Martínez Ortega
Sea cucumber detection represents an important step in underwater environmental perception, which is an indispensable part of the intelligent subsea fishing system. However, water turbidity decreases the clarity of underwater images, presenting a challen...
ver más
|
|
|
|
|
|