Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Xiangxiao Lei"'
Publikováno v:
Frontiers in Bioengineering and Biotechnology, Vol 12 (2024)
To address the low docking accuracy of existing robotic wheelchair/beds, this study proposes an automatic docking framework integrating light detection and ranging (LIDAR), visual positioning, and laser ranging. First, a mobile chassis was designed f
Externí odkaz:
https://doaj.org/article/7fdf629608be4c34bd3dbf9092be4f5b
Autor:
Xiangxiao Lei, Honglin Ouyang
Publikováno v:
IEEE Access, Vol 9, Pp 85455-85463 (2021)
Conventional fuzzy clustering algorithms present several disadvantages with respect to image segmentation, including a tendency to arrive at local optima and a relatively high sensitivity to noise and initial cluster centers. To address these issues,
Externí odkaz:
https://doaj.org/article/cc6ebd51996a4d3aa778586c5ac1a9ca
Publikováno v:
Ciência Rural, Vol 49, Iss 9
ABSTRACT: The use of machine vision to recognize mature pomegranates in natural environments is of major significance in improving the applicability and work efficiency of picking robots. By analyzing the color characteristics of color images of matu
Externí odkaz:
https://doaj.org/article/911d4d32a3384624a72c1c473129597a
Publikováno v:
Ciência Rural. 2019, Vol. 49 Issue 9, p1-8. 8p.
Autor:
Honglin Ouyang, Xiangxiao Lei
Publikováno v:
Cluster Computing. 22:13911-13921
Fuzzy clustering algorithm is the main method of image segmentation, but it can’t be widely used in various fields. Therefore, an image segmentation algorithm based on improved fuzzy clustering was proposed in this paper. The fuzzy clustering theor
Publikováno v:
Optical Engineering. 57:1
To improve the timeliness of the three-dimensional (3-D) maximum entropy method, an image segmentation method based on equivalent 3-D entropy and artificial fish swarm optimization algorithm is proposed. An equivalent 3-D entropy method without logar
Publikováno v:
Pattern Recognition & Image Analysis; Oct2019, Vol. 29 Issue 4, p592-597, 6p
Publikováno v:
Optical Engineering; Oct2018, Vol. 57 Issue 10, p1-7, 7p
Publikováno v:
Ciência Rural, Vol 49, Iss 9
Ciência Rural v.49 n.9 2019
Ciência Rural
Universidade Federal de Santa Maria (UFSM)
instacron:UFSM
Ciência Rural v.49 n.9 2019
Ciência Rural
Universidade Federal de Santa Maria (UFSM)
instacron:UFSM
EnglishThe use of machine vision to recognize mature pomegranates in natural environments is of major significance in improving the applicability and work efficiency of picking robots. By analyzing the color characteristics of color images of mature