Zobrazeno 21 - 30
of 67
pro vyhledávání: '"Xue-Song Tang"'
Publikováno v:
Neurocomputing. 396:314-323
Visual cortex is able to process information in multiple pathways and integrate various forms of representations. This paper proposed a bio-inspired method that utilizes the line-segment-based representation to perform a dedicated channel for the geo
Publikováno v:
Neurocomputing. 380:259-270
Fabric defect classification is traditionally achieved by human visual examination, which is inefficient and labor-intensive. Therefore, using intelligent and automated methods to solve this problem has become a hot research topic. With the increasin
Publikováno v:
IEEE Access, Vol 8, Pp 173158-173168 (2020)
In recent years, with the development of machine learning, especially after the rise of deep learning, time series clustering has been proven to effectively provide useful information in cloud computing and big data. However, many modern clustering a
Publikováno v:
IECON
Moth-flame optimization algorithms are widely employed to solve optimization problems and achieve good performance. However, the algorithms suffer the shortcoming of prematurity because of the early gathering of flames. To solve this problem, the fla
Publikováno v:
Expert Systems with Applications. 201:117176
Publikováno v:
Knowledge-Based Systems. 251:108885
Publikováno v:
IEEE Access, Vol 7, Pp 56713-56723 (2019)
In this paper, a new clustering algorithm is proposed based on cross clusters without using membership functions. In light of the cross clustering data transformation, the spatial distribution of data is changed while the original data dimension simu
Publikováno v:
IEEE Access, Vol 7, Pp 99-110 (2019)
Human beings have a strong capability to identify objects in different viewpoints. Unlike computer vision that requires sufficient training samples in various scales and rotations, biological visual systems can efficiently recognize objects in divers
Publikováno v:
Neurocomputing. 321:1-16
Dealing with high-dimensional dataset has always been an important problem and feature selection is one of useful tools. In this paper, we develop a new filter based supervised feature selection method by combining Trace Ratio Criterion of Linear Dis
Publikováno v:
Textile Research Journal. 89:3539-3555
The convolutional neural network (CNN) has recently achieved great breakthroughs in many computer vision tasks. However, its application in fabric texture defects classification has not been thoroughly researched. To this end, this paper carries out