|
|
|
|
|
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
|
|
|
|
|
|
|
|
|
|
|
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...
ver más
|
|
|
|
|
|
|
|
|
|
|
Wenhao Wang, Yun Shi, Wanfu Liu and Zijin Che
Rising labor costs and a workforce shortage have impeded the development and economic benefits of the global grape industry. Research and development of intelligent grape harvesting technologies is desperately needed. Therefore, rapid and accurate identi...
ver más
|
|
|
|
|
|
|
|
|
|
|
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
|
|
|
|
|
|
|
|
|
|
|
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
|
|
|
|
|
|
|
|
|
|
|
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
|
|
|
|
|
|
|
|
|
|
|
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
|
|
|
|
|
|
|
|
|
|
|
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
|
|
|
|
|
|
|
|
|
|
|
Wenji Yang and Xiaoying Qiu
The damage caused by pests to crops results in reduced crop yield and compromised quality. Accurate and timely pest detection plays a crucial role in helping farmers to defend against and control pests. In this paper, a novel crop pest detection model na...
ver más
|
|
|
|
|
|
|
|
|
|
|
Oscar Leonardo García-Navarrete, Oscar Santamaria, Pablo Martín-Ramos, Miguel Ángel Valenzuela-Mahecha and Luis Manuel Navas-Gracia
Corn (Zea mays L.) is one of the most important cereals worldwide. To maintain crop productivity, it is important to eliminate weeds that compete for nutrients and other resources. The eradication of these causes environmental problems through the use of...
ver más
|
|
|
|
|
|