Zobrazeno 1 - 10
of 72
pro vyhledávání: '"Zuojin Li"'
Publikováno v:
Sensors, Vol 23, Iss 24, p 9637 (2023)
Prosthetic attack is a problem that must be prevented in current finger vein recognition applications. To solve this problem, a finger vein liveness detection system was established in this study. The system begins by capturing short-term static fing
Externí odkaz:
https://doaj.org/article/c38ca721bce14539adf3076e6dbddf83
Publikováno v:
Applied Sciences, Vol 13, Iss 20, p 11222 (2023)
Vein segmentation and projection correction constitute the core algorithms of an auxiliary venipuncture device, responding to accurate venous positioning to assist puncture and reduce the number of punctures and pain of patients. This paper proposes
Externí odkaz:
https://doaj.org/article/a819a813c75b455184f4d315579f6eca
Publikováno v:
IEEE Access, Vol 7, Pp 179212-179219 (2019)
Fault diagnosis of pumping unit system has long been a challenging issue owing to the system that exhibits nonlinearity, coupled parameters and time-varying in the production process. In this paper, a novel fault diagnosis method based on dynamic axi
Externí odkaz:
https://doaj.org/article/84aaab684dc543e1b79d76ea5b5f9621
Publikováno v:
IEEE Access, Vol 7, Pp 155825-155834 (2019)
Desulfurization control of natural gas has long been a challenging industrial issue owing to its inherent difficulty in establishing accurate mathematical model for the nonlinear and strong coupling process. In this paper, a data-based adaptive dynam
Externí odkaz:
https://doaj.org/article/d08f08b7089c480e8613ea247f1e688e
Publikováno v:
International Journal of Distributed Sensor Networks, Vol 15 (2019)
The study of the robust fatigue feature learning method for the driver’s operational behavior is of great significance for improving the performance of the real-time detection system for driver’s fatigue state. Aiming at how to extract more abstr
Externí odkaz:
https://doaj.org/article/cb5626b35ff34a0e9540bbbd6725c103
Publikováno v:
Sensors, Vol 17, Iss 6, p 1212 (2017)
Fatigued driving is a major cause of road accidents. For this reason, the method in this paper is based on the steering wheel angles (SWA) and yaw angles (YA) information under real driving conditions to detect drivers’ fatigue levels. It analyzes
Externí odkaz:
https://doaj.org/article/9a059c9eeb994256be1fb5c330725dd3
Publikováno v:
Sensors, Vol 17, Iss 3, p 495 (2017)
This paper presents a drowsiness on-line detection system for monitoring driver fatigue level under real driving conditions, based on the data of steering wheel angles (SWA) collected from sensors mounted on the steering lever. The proposed system
Externí odkaz:
https://doaj.org/article/391eb074da5648dfa559c4b1a6f175ba
Publikováno v:
WSEAS TRANSACTIONS ON COMPUTERS. 21:283-293
This paper proposes a deep learning scheme to automatically carry out reading recognition in wheel mechanical water meter images. Aiming at these early water meters deployed in old residential compounds, this method based on deep neural networks empl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a0799a5f1165d52ed27ba3a1241dfafb
https://doi.org/10.37394/23205.2022.21.35
https://doi.org/10.37394/23205.2022.21.35
Publikováno v:
IEEE Transactions on Vehicular Technology. 71:269-281
In the field of advanced driver assistance systems (ADAS), effective learning of driver fatigue characteristics representation is a major challenge due to uncertainties of both real roads and drivers. To tackle this problem, this paper proposes a nov
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d6682b4e48e8430bacf1ec61e9279ecc
https://doi.org/10.1109/tvt.2021.3130152
https://doi.org/10.1109/tvt.2021.3130152
Publikováno v:
International Journal of Cognitive Informatics and Natural Intelligence. 15:1-19
Using thermal tactile sensing mechanism based on semi-infinite body model, and combining with the advantages of maximum proportional controller, fuzzy and PID controller, a thermal tactile perception and reproduction experiment device (TTPRED) was de
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::45083e5a2fc15f6b183856c775efae00
https://doi.org/10.4018/ijcini.20211001.oa22
https://doi.org/10.4018/ijcini.20211001.oa22