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Xinmin Li, Yingkun Wei, Jiahui Li, Wenwen Duan, Xiaoqiang Zhang and Yi Huang
Object detection in unmanned aerial vehicle (UAV) images has become a popular research topic in recent years. However, UAV images are captured from high altitudes with a large proportion of small objects and dense object regions, posing a significant cha...
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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...
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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...
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Boyu Liu, Hao Wang, Yongqiang Wang, Congling Zhou and Lei Cai
The recognition of lane line type plays an important role in the perception of advanced driver assistance systems (ADAS). In actual vehicle driving on roads, there are a variety of lane line type and complex road conditions which present significant chal...
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Ziwei Tian, Jie Huang, Yang Yang and Weiying Nie
Aerial remote sensing image object detection, based on deep learning, is of great significance in geological resource exploration, urban traffic management, and military strategic information. To improve intractable problems in aerial remote sensing imag...
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Jinnan Hu, Guo Li, Haolan Mo, Yibo Lv, Tingting Qian, Ming Chen and Shenglian Lu
The extraction and analysis of plant phenotypic characteristics are critical issues for many precision agriculture applications. An improved YOLOv5 model was proposed in this study for accurate node detection and internode length estimation of crops by u...
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Langyu Wang, Yan Zhang, Yahong Lin, Shuai Yan, Yuanyuan Xu and Bo Sun
Aiming at the problem of insufficient feature extraction, low precision, and recall in sea surface ship detection, a YOLOv5 algorithm based on lightweight convolution and attention mechanism is proposed. We combine the receptive field enhancement module ...
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Qixun Xiao, Wenying Zheng, Yifan He, Zijie Chen, Fanxin Meng and Liyan Wu
The use of Internet of Things (IoT) technology for real-time monitoring of agricultural pests is an unavoidable trend in the future of intelligent agriculture. This paper aims to address the difficulties in deploying models at the edge of the pest monito...
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Teng Gao and Xianwu Zhang
This work proposes a new approach based on YOLOX model enhancement for the helmet-wearing real-time detection task, which is plagued by low detection accuracy, incorrect detection, and missing detection. First, in the backbone network, recursive gated co...
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