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Xiao Chen, Mujiahui Yuan, Qi Yang, Haiyang Yao and Haiyan Wang
Underwater target detection using optical images is a challenging yet promising area that has witnessed significant progress. However, fuzzy distortions and irregular light absorption in the underwater environment often lead to image blur and color bias,...
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Yong Mei, Hao Chen and Shuting Yang
High-resolution remote sensing image building target detection has wide application value in the fields of land planning, geographic monitoring, smart cities and other fields. However, due to the complex background of remote sensing imagery, some detaile...
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Hao Li, Maosheng Hu and Youxin Huang
The identification of overpass structures in road networks has great significance for multi-scale modeling of roads, congestion analysis, and vehicle navigation. The traditional vector-based methods identify overpasses by the methodologies coming from co...
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Mingyu Zhang, Fei Gao, Wuping Yang and Haoran Zhang
In this paper, we propose a wildlife detection algorithm based on improved YOLOv5s by combining six real wildlife images of different sizes and forms as datasets. Firstly, we use the RepVGG model to simplify the network structure that integrates the idea...
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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...
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Junchi Zhou, Wenwu Hu, Airu Zou, Shike Zhai, Tianyu Liu, Wenhan Yang and Ping Jiang
Considering the high requirements of current kiwifruit picking recognition systems for mobile devices, including the small number of available features for image targets and small-scale aggregation, an enhanced YOLOX-S target detection algorithm for kiwi...
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Chenchen Gu, Chunjiang Zhao, Wei Zou, Shuo Yang, Hanjie Dou and Changyuan Zhai
Orchard spraying can effectively control pests and diseases. Over-spraying commonly results in excessive pesticide residues on agricultural products and environmental pollution. To avoid these problems, variable spraying technology uses target canopy det...
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Kaiyue Liu, Qi Sun, Daming Sun, Lin Peng, Mengduo Yang and Nizhuan Wang
Underwater target detection is a crucial aspect of ocean exploration. However, conventional underwater target detection methods face several challenges such as inaccurate feature extraction, slow detection speed, and lack of robustness in complex underwa...
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Hui Zhou, Peng Chen, Yingqiu Li and Bo Wang
Ship detection in large-scene offshore synthetic aperture radar (SAR) images is crucial in civil and military fields, such as maritime management and wartime reconnaissance. However, the problems of low detection rates, high false alarm rates, and high m...
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Fujun Du, Shuangjian Jiao and Kaili Chu
To ensure the safety and rational use of bridge traffic lines, the existing bridge structural damage detection models are not perfect for feature extraction and have difficulty meeting the practicability of detection equipment. Based on the YOLO (You Onl...
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Junchi Zhou, Ping Jiang, Airu Zou, Xinglin Chen and Wenwu Hu
In order to realize the real-time detection of an unmanned fishing speedboat near a ship ahead, a perception platform based on a target visual detection system was established. By controlling the depth and width of the model to analyze and compare traini...
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Hailiang Gong, Xi Wang and Weidong Zhuang
This study focuses on real-time detection of maize crop rows using deep learning technology to meet the needs of autonomous navigation for weed removal during the maize seedling stage. Crop row recognition is affected by natural factors such as soil expo...
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Xiang Sun, Yisheng Miao, Xiaoyan Wu, Yuansheng Wang, Qingxue Li, Huaji Zhu and Huarui Wu
To enhance the transplantation effectiveness of vegetables and promptly formulate subsequent work strategies, it is imperative to study the recognition approach for transplanted seedlings. In the natural and complex environment, factors like background a...
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Jizhong Deng, Chang Yang, Kanghua Huang, Luocheng Lei, Jiahang Ye, Wen Zeng, Jianling Zhang, Yubin Lan and Yali Zhang
The realization that mobile phones can detect rice diseases and insect pests not only solves the problems of low efficiency and poor accuracy from manually detection and reporting, but it also helps farmers detect and control them in the field in a timel...
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Liang Chen, Yuyi Yang, Zhenheng Wang, Jian Zhang, Shaowu Zhou and Lianghong Wu
Underwater robot perception is a critical task. Due to the complex underwater environment and low quality of optical images, it is difficult to obtain accurate and stable target position information using traditional methods, making it unable to meet pra...
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Shilin Li, Shujuan Zhang, Jianxin Xue, Haixia Sun and Rui Ren
The efficient identification of the field flat jujube is the first condition to realize its automated picking. Consequently, a lightweight algorithm of target identification based on improved YOLOv5 (you only look once) is proposed to meet the requiremen...
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Jefferson T. Hinke, Louise M. Giuseffi, Victoria R. Hermanson, Samuel M. Woodman and Douglas J. Krause
Estimating seabird and pinniped abundance is central to wildlife management and ecosystem monitoring in Antarctica. Unoccupied aerial systems (UAS) can collect images to support monitoring, but manual image analysis is often impractical. Automating targe...
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Tianqi Qiu, Xiaojin Liang, Qingyun Du, Fu Ren, Pengjie Lu and Chao Wu
Emergency remote sensing mapping can provide support for decision making in disaster assessment or disaster relief, and therefore plays an important role in disaster response. Traditional emergency remote sensing mapping methods use decryption algorithms...
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Zhao Xiong and Jiang Wu
Malaria is one of the major global health threats. Microscopic examination has been designated as the ?gold standard? for malaria detection by the World Health Organization. However, it heavily relies on the experience of doctors, resulting in long diagn...
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Hua Yang, Xingquan Deng, Hao Shen, Qingfeng Lei, Shuxiang Zhang and Neng Liu
In recent years, the domain of diagnosing plant afflictions has predominantly relied upon the utilization of deep learning techniques for classifying images of diseased specimens; however, these classification algorithms remain insufficient for instances...
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