Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Nhat Minh Chung"'
DAKRS: Domain Adaptive Knowledge-Based Retrieval System for Natural Language-Based Vehicle Retrieval
Publikováno v:
IEEE Access, Vol 11, Pp 90951-90965 (2023)
Given Natural Language (NL) text descriptions, NL-based vehicle retrieval aims to extract target vehicles from a multi-view multi-camera traffic video pool. Solutions to the problem have been challenged by not only inherent distinctions between textu
Externí odkaz:
https://doaj.org/article/4db103a1c6fb4900aeca6c698864fa51
Publikováno v:
Sensors, Vol 20, Iss 23, p 6973 (2020)
Decades of ongoing research have shown that background modelling is a very powerful technique, which is used in intelligent surveillance systems, in order to extract features of interest, known as foregrounds. In order to work with the dynamic nature
Externí odkaz:
https://doaj.org/article/fb1c715aa0a046ddb485fa78076bad0c
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Autor:
Huy Dinh-Anh Le, Quang Qui-Vinh Nguyen, Vuong Ai Nguyen, Thong Duy-Minh Nguyen, Nhat Minh Chung, Tin-Trung Thai, Synh Viet-Uyen Ha
Publikováno v:
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).
Autor:
Nhat Minh Chung, Huy Dinh-Anh Le, Vuong Ai Nguyen, Quang Qui-Vinh Nguyen, Thong Duy-Minh Nguyen, Tin-Trung Thai, Synh Viet-Uyen Ha
Publikováno v:
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).
Autor:
Tin-Trung Thai, Synh Viet-Uyen Ha, Thong Duy-Minh Nguyen, Huy Dinh-Anh Le, Nhat Minh Chung, Quang Qui-Vinh Nguyen, Vuong Ai-Nguyen
Publikováno v:
Intelligent Information and Database Systems ISBN: 9783031217425
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::73abe6c48d580f0ab534ed7b74db1594
https://doi.org/10.1007/978-3-031-21743-2_22
https://doi.org/10.1007/978-3-031-21743-2_22
Publikováno v:
RIVF
The main goal of traffic surveillance systems (TSSs) is to extract useful traffic information by analyzing signals from cameras. This paper presents a system for vehicle detection and classification from static pole-mounted roadside surveillance came
Publikováno v:
RIVF
Shadows are among the most critical problems for traffic surveillance systems (TSSs). In a TSS, shadow regions significantly affect the extraction of vehicles’ attributes for vehicle detection, classification and tracking. Although many methods hav
Publikováno v:
APCC
Traffic surveillance system (TSS) is an essential tool to extract necessary information (count, type, speed, etc.) from cameras for traffic monitoring in many metro cities. In TSS, vehicle detection plays a pivotal role as it is a vital process for f
Publikováno v:
Sensors (Basel, Switzerland)
Sensors
Volume 20
Issue 23
Sensors, Vol 20, Iss 6973, p 6973 (2020)
Sensors
Volume 20
Issue 23
Sensors, Vol 20, Iss 6973, p 6973 (2020)
Decades of ongoing research have shown that background modelling is a very powerful technique, which is used in intelligent surveillance systems, in order to extract features of interest, known as foregrounds. In order to work with the dynamic nature