Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Xue-Song Tang"'
Publikováno v:
IEEE Transactions on Cognitive and Developmental Systems. 13:503-513
In modern textile industrial processes, textile defect recognition and classification are of vital importance for textile quality control. Recently, as the critical machine-learning method, the deep convolutional neural network (CNN) has shown superi
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:
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
Publikováno v:
2020 Chinese Automation Congress (CAC).
The teleoperating system has the shortcomings of the limited instruction set and low control efficiency, which cannot efficiently complete complex tasks. To solve this problem, this paper proposes a robot shared control method based on the adaptive n
Publikováno v:
2018 Chinese Automation Congress (CAC).
The ability of adjusting policy is the key to learning decision making when completing complex manipulation tasks for agents. To solve this problem with the consideration of both exploration and exploitation, we propose a novel deep reinforcement lea
Publikováno v:
Artificial Intelligence on Fashion and Textiles ISBN: 9783319996943
Considering that the traditional detection of fabric defect can be time-consuming and less-efficient, a modified faster regional-based convolutional network method (Faster RCNN) based on the VGG structure is proposed. In the paper, we improved the Fa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::acaf6d895070b436420bc417924e7171
https://doi.org/10.1007/978-3-319-99695-0_6
https://doi.org/10.1007/978-3-319-99695-0_6
Publikováno v:
ASCC
According to the idea of deep learning, this paper designs a new multilayer long short-term memory (LSTM) network method, a data driven model for sequence modeling. We use this deep neural network to solve the reconstruction problem of Single Measure
Publikováno v:
Remote Sensing; Volume 9; Issue 5; Pages: 508
Remote Sensing, Vol 9, Iss 5, p 508 (2017)
Remote Sensing, Vol 9, Iss 5, p 508 (2017)
Nowadays, 3D imaging of plants not only contributes to monitoring and managing plant growth, but is also becoming an essential part of high-throughput plant phenotyping. In this paper, an inexpensive (less than 70 USD) and portable platform with bino
Publikováno v:
Sensors, Vol 18, Iss 11, p 3625 (2018)
Sensors
Volume 18
Issue 11
Sensors (Basel, Switzerland)
Sensors
Volume 18
Issue 11
Sensors (Basel, Switzerland)
Leaves account for the largest proportion of all organ areas for most kinds of plants, and are comprise the main part of the photosynthetically active material in a plant. Observation of individual leaves can help to recognize their growth status and