Zobrazeno 1 - 10
of 33
pro vyhledávání: '"Yuncheng Zhou"'
Publikováno v:
Frontiers in Plant Science, Vol 15 (2024)
Common object detection and image segmentation methods are unable to accurately estimate the shape of the occluded fruit. Monitoring the growth status of shaded crops in a specific environment is challenging, and certain studies related to crop harve
Externí odkaz:
https://doaj.org/article/754ee9011f834c5bb034820efc38b0bf
Publikováno v:
ACS Omega, Vol 9, Iss 6, Pp 6994-7002 (2024)
Externí odkaz:
https://doaj.org/article/8dabd4456c4d4948b72f2f6d6c4e4228
Autor:
Dabao Wang, Zhi Song, Teng Miao, Chao Zhu, Xin Yang, Tao Yang, Yuncheng Zhou, Hanbing Den, Tongyu Xu
Publikováno v:
Frontiers in Plant Science, Vol 14 (2023)
The 3D point cloud data are used to analyze plant morphological structure. Organ segmentation of a single plant can be directly used to determine the accuracy and reliability of organ-level phenotypic estimation in a point-cloud study. However, it is
Externí odkaz:
https://doaj.org/article/5a24d191ce0b4cad9b6cfc10e401c656
Autor:
Haipeng Xiao, Miguel Angel Sotelo, Yulin Ma, Bo Cao, Yuncheng Zhou, Youchun Xu, Rendong Wang, Zhixiong Li
Publikováno v:
IEEE Access, Vol 8, Pp 101514-101527 (2020)
Long Short-Term Memory (LSTM) neural network has been widely used in many applications, but its application in classification of vehicle movement patterns is still limited. In this paper, LSTM is applied to the vehicle behavior recognition problem to
Externí odkaz:
https://doaj.org/article/a189e4d5a67c4ef8b9716514a1d25618
Autor:
Yechong Huang, Jiahang Xu, Yuncheng Zhou, Tong Tong, Xiahai Zhuang, the Alzheimer’s Disease Neuroimaging Initiative (ADNI)
Publikováno v:
Frontiers in Neuroscience, Vol 13 (2019)
Alzheimer’s disease (AD) is one of the most common neurodegenerative diseases. In the last decade, studies on AD diagnosis has attached great significance to artificial intelligence-based diagnostic algorithms. Among the diverse modalities of imagi
Externí odkaz:
https://doaj.org/article/57a6d42626ef4275a36230c2d75fd1a4
Publikováno v:
Sensors, Vol 20, Iss 3, p 812 (2020)
Image segmentation is one of the most important methods for animal phenome research. Since the advent of deep learning, many researchers have looked at multilayer convolutional neural networks to solve the problems of image segmentation. A network si
Externí odkaz:
https://doaj.org/article/4cf59ae435de42b1b28cea5310cbe4f3
Publikováno v:
Journal of Materials Chemistry A; 11/21/2024, Vol. 12 Issue 43, p29735-29748, 14p
Autor:
Jiechen Song, Yuxing Xu, Yuncheng Zhou, Pengfei Wang, Hailan Feng, Jun Yang, Fuchang Zhuge, Qiangqiang Tan
Publikováno v:
ACS Applied Materials & Interfaces. 15:20897-20908
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d7f249a87ee1e523a64fbdc79c697dd2
https://doi.org/10.1021/acsami.2c22562
https://doi.org/10.1021/acsami.2c22562
Autor:
Xueqian Ji, Yuxing Xu, Qing Xia, Yuncheng Zhou, Jiechen Song, Hailan Feng, Pengfei Wang, Jun Yang, Qiangqiang Tan
Publikováno v:
ACS Applied Materials & Interfaces. 14:30133-30143
With the increasing demand for high energy density and rapid charging performance, Li-rich materials have been the up and coming cathodes for next-generation lithium-ion batteries. However, because of oxygen evolution and structural instability, the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6155a305be3ff9495cf6b39dedf8fb99
https://doi.org/10.1021/acsami.2c03073
https://doi.org/10.1021/acsami.2c03073
Autor:
Tingxuan Xu, Duanfeng Chu, Zheng Sifa, Chuan Sun, Yicheng Li, Yuncheng Zhou, Yulin Ma, Junru Yang
Publikováno v:
Journal of Intelligent Manufacturing. 32:1249-1269
As the complex driving scenarios bring about an opportunity for application of deep learning in safe driving, artificial intelligence based on deep learning has become a heatedly discussed topic in the field of advanced driving assistance system. Thi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::453510714032b4f5403f8aab259ad402
https://doi.org/10.1007/s10845-020-01605-x
https://doi.org/10.1007/s10845-020-01605-x