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Rujia Li, Yadong Li, Weibo Qin, Arzlan Abbas, Shuang Li, Rongbiao Ji, Yehui Wu, Yiting He and Jianping Yang
This research tackles the intricate challenges of detecting densely distributed maize leaf diseases and the constraints inherent in YOLO-based detection algorithms. It introduces the GhostNet_Triplet_YOLOv8s algorithm, enhancing YOLO v8s by integrating t...
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Chenglin Wang, Qiyu Han, Jianian Li, Chunjiang Li and Xiangjun Zou
Blueberry is among the fruits with high economic gains for orchard farmers. Identification of blueberry fruits with different maturities has economic significance to help orchard farmers plan pesticide application, estimate yield, and conduct harvest ope...
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Zhengyang Zhong, Lijun Yun, Feiyan Cheng, Zaiqing Chen and Chunjie Zhang
This paper proposes a lightweight and efficient mango detection model named Light-YOLO based on the Darknet53 structure, aiming to rapidly and accurately detect mango fruits in natural environments, effectively mitigating instances of false or missed det...
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Junyi Chen, Yanyun Shen, Yinyu Liang, Zhipan Wang and Qingling Zhang
Aircraft detection in SAR images of airports remains crucial for continuous ground observation and aviation transportation scheduling in all weather conditions, but low resolution and complex scenes pose unique challenges. Existing methods struggle with ...
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Baobao Liu, Heying Wang, Zifan Cao, Yu Wang, Lu Tao, Jingjing Yang and Kaibing Zhang
Defect detection holds significant importance in improving the overall quality of fabric manufacturing. To improve the effectiveness and accuracy of fabric defect detection, we propose the PRC-Light YOLO model for fabric defect detection and establish a ...
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Guoyu Zhang, Ye Tian, Wenhan Yin and Change Zheng
The use of automation technology in agriculture has become particularly important as global agriculture is challenged by labor shortages and efficiency gains. The automated process for harvesting apples, an important agricultural product, relies on effic...
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Siyi Zhou, Kewei Cai, Yanhong Feng, Xiaomeng Tang, Hongshuai Pang, Jiaqi He and Xiang Shi
In aquaculture, the accurate recognition of fish underwater has outstanding academic value and economic benefits for scientifically guiding aquaculture production, which assists in the analysis of aquaculture programs and studies of fish behavior. Howeve...
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Ruoyu Chen and Ying Chen
To detect a desired underwater target quickly and precisely, a real-time sonar-based target detection system mounted on an autonomous underwater helicopter (AUH) using an improved convolutional neural network (CNN) is proposed in this paper. YOLOv5 is in...
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Wang Yang, Junhui Xi, Zhihao Wang, Zhiheng Lu, Xian Zheng, Debang Zhang and Yu Huang
Cassava (Manihot esculenta Crantz) is a major tuber crop worldwide, but its mechanized harvesting is inefficient. The digging?pulling cassava harvester is the primary development direction of the cassava harvester. However, the harvester clamping?pulling...
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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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