213   Artículos

 
en línea
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... ver más
Revista: Agriculture    Formato: Electrónico

 
en línea
Yishen Lin, Zifan Huang, Yun Liang, Yunfan Liu and Weipeng Jiang    
Citrus fruits hold pivotal positions within the agricultural sector. Accurate yield estimation for citrus fruits is crucial in orchard management, especially when facing challenges of fruit occlusion due to dense foliage or overlapping fruits. This study... ver más
Revista: Agriculture    Formato: Electrónico

 
en línea
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 ... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
JongBae Kim    
This technology can prevent accidents involving large vehicles, such as trucks or buses, by selecting an optimal driving lane for safe autonomous driving. This paper proposes a method for detecting forward-driving vehicles within road images obtained fro... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
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 ... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
Qing Dong, Lina Sun, Tianxin Han, Minqi Cai and Ce Gao    
Timely and effective pest detection is essential for agricultural production, facing challenges such as complex backgrounds and a vast number of parameters. Seeking solutions has become a pressing matter. This paper, based on the YOLOv5 algorithm, develo... ver más
Revista: Agriculture    Formato: Electrónico

 
en línea
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... ver más
Revista: Agriculture    Formato: Electrónico

 
en línea
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... ver más
Revista: Agronomy    Formato: Electrónico

 
en línea
Yi Yang, Guankang Zhang, Shutao Ma, Zaihua Wang, Houcheng Liu and Song Gu    
The accurate detection and counting of flowers ensure the grading quality of the ornamental plants. In automated potted flower grading scenarios, low detection precision, occlusions and overlaps impact counting accuracy. This study proposed a counting me... ver más
Revista: Agronomy    Formato: Electrónico

 
en línea
Zhou Fang, Xiaoyong Wang, Liang Zhang and Bo Jiang    
Currently, deep learning is extensively utilized for ship target detection; however, achieving accurate and real-time detection of multi-scale targets remains a significant challenge. Considering the diverse scenes, varied scales, and complex backgrounds... ver más
Revista: Journal of Marine Science and Engineering    Formato: Electrónico

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