Zobrazeno 1 - 10
of 126
pro vyhledávání: '"Juntao Xiong"'
Autor:
Juntao Xiong, Youcong Hou, Hang Wang, Kun Tang, Kangning Liao, Yuanhua Yao, Lan Liu, Ye Zhang
Publikováno v:
Agronomy, Vol 14, Iss 10, p 2347 (2024)
Curing modulation is one of the important processes in tobacco production, so it is crucial to recognize tobacco flue-curing states effectively and accurately. This study created a dataset of the complete tobacco flue-curing process in a bulk curing
Externí odkaz:
https://doaj.org/article/465c68c733b74f4990a43f6ba9fb2b18
Publikováno v:
Agronomy, Vol 14, Iss 9, p 1988 (2024)
The global agriculture industry is encountering challenges due to labor shortages and the demand for increased efficiency. Currently, fruit yield estimation in guava orchards primarily depends on manual counting. Machine vision is an essential techno
Externí odkaz:
https://doaj.org/article/278f70d17e484d7aad436d3a073bd5e5
Publikováno v:
Agronomy, Vol 13, Iss 7, p 1674 (2023)
A method for counting the number of citrus fruits based on the improved YOLOv5s algorithm combined with the DeepSort tracking algorithm is proposed to address the problem of the low accuracy of counting citrus fruits due to shading and lighting facto
Externí odkaz:
https://doaj.org/article/bd86857db8114f52931f9558f72b107d
Autor:
Chenglin Wang, Suchun Liu, Yawei Wang, Juntao Xiong, Zhaoguo Zhang, Bo Zhao, Lufeng Luo, Guichao Lin, Peng He
Publikováno v:
Frontiers in Plant Science, Vol 13 (2022)
As one of the representative algorithms of deep learning, a convolutional neural network (CNN) with the advantage of local perception and parameter sharing has been rapidly developed. CNN-based detection technology has been widely used in computer vi
Externí odkaz:
https://doaj.org/article/c2d6ea12e9e8466e94ff8012ffd44b96
Publikováno v:
IEEE Access, Vol 8, Pp 164546-164555 (2020)
Litchi is often harvested by clamping and cutting the branches, which are small and can easily be damaged by the picking robot. Therefore, the detection of litchi branches is particularly significant. In this article, an fully convolutional neural ne
Externí odkaz:
https://doaj.org/article/247bc8c866e14be5b2cbe892861382c8
A Method of Green Citrus Detection in Natural Environments Using a Deep Convolutional Neural Network
Autor:
Zhenhui Zheng, Juntao Xiong, Huan Lin, Yonglin Han, Baoxia Sun, Zhiming Xie, Zhengang Yang, Chenglin Wang
Publikováno v:
Frontiers in Plant Science, Vol 12 (2021)
The accurate detection of green citrus in natural environments is a key step in realizing the intelligent harvesting of citrus through robotics. At present, the visual detection algorithms for green citrus in natural environments still have poor accu
Externí odkaz:
https://doaj.org/article/2415eefcad564cbf9617a11c6985209d
Autor:
Xiaolang Chen, Tianlong Yang, Kaizhan Mai, Caixing Liu, Juntao Xiong, Yingjie Kuang, Yuefang Gao
Publikováno v:
Animals, Vol 12, Iss 8, p 1047 (2022)
In precision dairy farming, computer vision-based approaches have been widely employed to monitor the cattle conditions (e.g., the physical, physiology, health and welfare). To this end, the accurate and effective identification of individual cow is
Externí odkaz:
https://doaj.org/article/261c2dee962346f68eac2f8f6fbe30dd
Publikováno v:
Sensors, Vol 19, Iss 2, p 428 (2019)
Fruit detection in real outdoor conditions is necessary for automatic guava harvesting, and the branch-dependent pose of fruits is also crucial to guide a robot to approach and detach the target fruit without colliding with its mother branch. To cond
Externí odkaz:
https://doaj.org/article/607ec852a85649959b142e23a1ea7fcd
Publikováno v:
Sensors, Vol 18, Iss 4, p 969 (2018)
Night-time fruit-picking technology is important to picking robots. This paper proposes a method of night-time detection and picking-point positioning for green grape-picking robots to solve the difficult problem of green grape detection and picking
Externí odkaz:
https://doaj.org/article/3c181cd548bd44a5879ab86b5f68b254
Publikováno v:
Sensors, Vol 18, Iss 3, p 700 (2018)
The non-destructive testing of litchi fruit is of great significance to the fresh-keeping, storage and transportation of harvested litchis. To achieve quick and accurate micro-damage detection, a non-destructive grading test method for litchi fruits
Externí odkaz:
https://doaj.org/article/6e48aa52cab441e5997a064d7bb41949