48   Artículos

 
en línea
Yu Zhang, Jiajun Niu, Zezhong Huang, Chunlei Pan, Yueju Xue and Fengxiao Tan    
An algorithm model based on computer vision is one of the critical technologies that are imperative for agriculture and forestry planting. In this paper, a vision algorithm model based on StyleGAN and improved YOLOv5s is proposed to detect sandalwood tre... ver más
Revista: Agriculture    Formato: Electrónico

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

 
en línea
Xingdong Sun, Yukai Zheng, Delin Wu and Yuhang Sui    
The key technology of automated apple harvesting is detecting apples quickly and accurately. The traditional detection methods of apple detection are often slow and inaccurate in unstructured orchards. Therefore, this article proposes an improved YOLOv5s... ver más
Revista: Agronomy    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
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
Revista: Agronomy    Formato: Electrónico

 
en línea
Ping Dong, Kuo Li, Ming Wang, Feitao Li, Wei Guo and Haiping Si    
In addition to the conventional situation of detecting a single disease on a single leaf in corn leaves, there is a complex phenomenon of multiple diseases overlapping on a single leaf (compound diseases). Current research on corn leaf disease detection ... ver más
Revista: Agriculture    Formato: Electrónico

 
en línea
Kai Sun, Ziyin Wu, Mingwei Wang, Jihong Shang, Zhihao Liu, Dineng Zhao and Xiaowen Luo    
Polymetallic nodules are spherical or ellipsoidal mineral aggregates formed naturally in deep-sea environments. They contain a variety of metallic elements and are important solid mineral resources on the seabed. How best to quickly and accurately identi... ver más
Revista: Journal of Marine Science and Engineering    Formato: Electrónico

 
en línea
Li Sun, Jingfa Yao, Hongbo Cao, Haijiang Chen and Guifa Teng    
In agricultural production, rapid and accurate detection of peach blossom bloom plays a crucial role in yield prediction, and is the foundation for automatic thinning. The currently available manual operation-based detection and counting methods are extr... ver más
Revista: Agriculture    Formato: Electrónico

 
en línea
Haojie Wang, Pingqing Fan, Xipei Ma and Yansong Wang    
The intelligent identification of coal gangue on industrial conveyor belts is a crucial technology for the precise sorting of coal gangue. To address the issues in coal gangue detection algorithms, such as high false negative rates, complex network struc... ver más
Revista: Algorithms    Formato: Electrónico

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

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