Zobrazeno 1 - 10
of 126
pro vyhledávání: '"Xiuyang Zhao"'
Publikováno v:
Machine Learning with Applications, Vol 15, Iss , Pp 100523- (2024)
Self-service shopping technologies have become commonplace in modern society. Although various innovative solutions have been adopted, there is still a gap in providing efficient services to consumers. Recent developments in mobile application techno
Externí odkaz:
https://doaj.org/article/1dab1244785f48c19e1230a2059c0eca
Autor:
Irfan Yaqoob, Muhammad Umair Hassan, Dongmei Niu, Xiuyang Zhao, Ibrahim A. Hameed, Saeed-Ul Hassan
Publikováno v:
ICT Express, Vol 9, Iss 5, Pp 809-814 (2023)
We argue that accurate person re-identification is a vital problem for urban public monitoring systems in the smart city context. Since images captured from different cameras have arbitrary resolutions resulting in resolution mismatch, this work prop
Externí odkaz:
https://doaj.org/article/84b5e6ccd8834009bab54ee5b6461c94
Publikováno v:
IET Computer Vision, Vol 14, Iss 1, Pp 36-47 (2020)
The detection of 3D interest points is a central problem in computer graphics, computer vision, and pattern recognition. It is also an important preprocessing step in the analysis of 3D model matching. Although studied for decades, detecting 3D inter
Externí odkaz:
https://doaj.org/article/56f0d4b252634b26a37577b53faa7c9c
Publikováno v:
IET Computer Vision, Vol 12, Iss 6, Pp 806-816 (2018)
Point set registration is a fundamental problem in many domains of computer vision. In previous work on the registration, the point sets are often represented using Gaussian mixture models and the registration process is represented as a form of a pr
Externí odkaz:
https://doaj.org/article/ce73813a3e9c45cda714d45c52f19806
Publikováno v:
IET Computer Vision, Vol 12, Iss 5, Pp 563-569 (2018)
Content‐based image retrieval (CBIR) is a research hotspot. To improve the performance of a CBIR system, especially the retrieval accuracy, this work proposes a method that uses a soft hypergraph combined with a weighted adjacent structure (WAS) to
Externí odkaz:
https://doaj.org/article/d5e45fb223cd471d9e61a9d97ba41c75
Publikováno v:
Sensors, Vol 21, Iss 6, p 2052 (2021)
In this paper, a deep learning-based traffic state discrimination method is proposed to detect traffic congestion at urban intersections. The detection algorithm includes two parts, global speed detection and a traffic state discrimination algorithm.
Externí odkaz:
https://doaj.org/article/45f510ccd6d743ebbf3aa3b1d357b91b
Publikováno v:
IEEE Transactions on Circuits and Systems for Video Technology. 33:771-781
Publikováno v:
Information Sciences. 616:1-15
Publikováno v:
Multimedia Tools and Applications. 82:16881-16904
Publikováno v:
Multimedia Tools and Applications. 82:389-405