|
|
|
|
|
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
|
|
|
|
|
|
|
|
|
|
|
Zhikai Jiang, Li Su and Yuxin Sun
Accurate ship object detection ensures navigation safety and effective maritime traffic management. Existing ship target detection models often have the problem of missed detection in complex marine environments, and it is hard to achieve high accuracy a...
ver más
|
|
|
|
|
|
|
|
|
|
|
Junsheng Liu, Guangze Zhao, Shuangxi Liu, Yi Liu, Huawei Yang, Jingwei Sun, Yinfa Yan, Guoqiang Fan, Jinxing Wang and Hongjian Zhang
In the realm of automated apple picking operations, the real-time monitoring of apple maturity and diameter characteristics is of paramount importance. Given the constraints associated with feature detection of apples in automated harvesting, this study ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Juanli Jing, Menglin Zhai, Shiqing Dou, Lin Wang, Binghai Lou, Jichi Yan and Shixin Yuan
The accurate identification of citrus fruits is important for fruit yield estimation in complex citrus orchards. In this study, the YOLOv7-tiny-BVP network is constructed based on the YOLOv7-tiny network, with citrus fruits as the research object. This n...
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
|
|
|
|
|
|
|
|
|
|
|
Fei Wu, Yitao Zhang, Lang Wang, Qiu Hu, Shengli Fan and Weiming Cai
The species and population size of marine fish are important for maintaining the ecological environment and reflecting climate change. Traditional fish detection methods mainly rely on manual or traditional computer vision, which has disadvantages such a...
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
|
|
|
|
|
|
|
|
|
|
|
Ziyi Li, Yang Li, Yanping Wang, Guangda Xie, Hongquan Qu and Zhuoyang Lyu
With the rapid development of deep learning, more and more complex models are applied to 3D point cloud object detection to improve accuracy. In general, the more complex the model, the better the performance and the greater the computational resource co...
ver más
|
|
|
|
|
|
|
|
|
|
|
Chuanyun Wang, Linlin Meng, Qian Gao, Jingjing Wang, Tian Wang, Xiaona Liu, Furui Du, Linlin Wang and Ershen Wang
Aiming at the problems of low detection accuracy and large computing resource consumption of existing Unmanned Aerial Vehicle (UAV) detection algorithms for anti-UAV, this paper proposes a lightweight UAV swarm detection method based on You Only Look Onc...
ver más
|
|
|
|
|
|
|
|
|
|
|
Lei Shi, Jiayue Sun, Yuanbo Dang, Shaoqi Zhang, Xiaoyun Sun, Lei Xi and Jian Wang
Utilizing image data for yield estimation is a key topic in modern agriculture. This paper addresses the difficulty of counting wheat spikelets using images, to improve yield estimation in wheat fields. A wheat spikelet image dataset was constructed with...
ver más
|
|
|
|
|
|