Zobrazeno 1 - 10
of 219
pro vyhledávání: '"Yongjie CUI"'
Publikováno v:
Journal of Agricultural Engineering, Vol 55, Iss 4 (2024)
A method combining experimental and simulation optimization was used to calibrate parameters to enhance the accuracy of discrete element model parameters during kiwifruit stem separation. First, physical experiments were conducted to determine the in
Externí odkaz:
https://doaj.org/article/d3128f3d84114dd58488633dbe9dc6c4
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 17739-17752 (2024)
Many current satellite-derived bathymetry methods usually rely on in-situ water depth, which limits their applications. In this study, an ICESat-2 assisted dual-band model (IDBM) is proposed, which can be used to derive bathymetry independent of in-s
Externí odkaz:
https://doaj.org/article/c231f7f604f24caaaa32a2bec1fcdcd7
Autor:
Ruizhe Yang, Zhenchao Wu, Wentai Fang, Hongliang Zhang, Wenqi Wang, Longsheng Fu, Yaqoob Majeed, Rui Li, Yongjie Cui
Publikováno v:
Information Processing in Agriculture, Vol 10, Iss 1, Pp 1-10 (2023)
Accurate and fast detection of abnormal hydroponic lettuce leaves is primary technology for robotic sorting. Yellow and rotten leaves are main types of abnormal leaves in hydroponic lettuce. This study aims to demonstrate a feasibility of detecting y
Externí odkaz:
https://doaj.org/article/1992521809644c06a01bf52d7ad3256b
Autor:
Kangkang Qi, Zhen Yang, Zhichao Liang, Yangyang Fan, Hao Xu, Yundong Wu, Binbin Wang, Yongjie Cui, Shuai Wang
Publikováno v:
IEEE Access, Vol 11, Pp 133340-133350 (2023)
To address challenges in manual detection of electronic component defects in facility greenhouses, this paper presents an electronic component defect detection method using the Improved YOLOv5 recognition algorithm. By introducing the Convolutional B
Externí odkaz:
https://doaj.org/article/8b9c12604b894d06ace59fe9f8181c96
Publikováno v:
Zhongguo youzhi, Vol 47, Iss 1, Pp 89-94 (2022)
为了拓展生物柴油原料来源，以气生微藻Heveochlorella sp. Yu为研究对象，通过测定其生长曲线、生物量、油脂产率、沉降率等，对其作为生物柴油生产原料的特性进行研究。结果表明，培养后
Externí odkaz:
https://doaj.org/article/c7ac50d60d164cfeaf71bd9304e70402
Publikováno v:
Sensors, Vol 23, Iss 17, p 7570 (2023)
To address the issue of low positioning accuracy of mobile robots in trellis kiwifruit orchards with weak signal environments, this study investigated an outdoor integrated positioning method based on ultra-wideband (UWB), light detection and ranging
Externí odkaz:
https://doaj.org/article/c8572fd68ca24524bd3fe641f33387d3
Autor:
Xiangchuan Meng, Zheren Cai, Yanyan Zhang, Xiaotian Hu, Zhi Xing, Zengqi Huang, Zhandong Huang, Yongjie Cui, Ting Hu, Meng Su, Xunfan Liao, Lin Zhang, Fuyi Wang, Yanlin Song, Yiwang Chen
Publikováno v:
Nature Communications, Vol 11, Iss 1, Pp 1-10 (2020)
Flexible perovskite solar cells suffer huge efficiency loss upon area scale-up due to brittleness of ITO and poor perovskite film quality. Here Meng et al. solve this by inserting a conductive and glued polymer layer between ITO and perovskite layers
Externí odkaz:
https://doaj.org/article/4fc5c7e742e748c9ac429d68f65ba3ce
Publikováno v:
Information Processing in Agriculture, Vol 7, Iss 1, Pp 58-71 (2020)
The harvesting of fresh kiwifruit is a labor-intensive operation that accounts for more than 25% of annual production costs. Mechanized harvesting technologies are thus being developed to reduce labor requirements for harvesting kiwifruit. To improve
Externí odkaz:
https://doaj.org/article/c351c31a6a9d42e589b4956e7a268276
Publikováno v:
Agronomy, Vol 12, Iss 12, p 3096 (2022)
Kiwifruit harvesting with robotics can be troublesome due to the clustering feature. The gripper of the end effector will easily cause unstable fruit grasping, or the bending and separation action will interfere with the neighboring fruit because of
Externí odkaz:
https://doaj.org/article/57d326206bb44ed58bad0f0d3057b1b6
Publikováno v:
IEEE Access, Vol 8, Pp 2327-2336 (2020)
This study presents a novel method to apply the RGB-D (Red Green Blue-Depth) sensors and fuse aligned RGB and NIR images with deep convolutional neural networks (CNN) for fruit detection. It aims to build a more accurate, faster, and more reliable fr
Externí odkaz:
https://doaj.org/article/a19608e1fa3a41b89c7ea2b34c69e519