Zobrazeno 1 - 10
of 2 005
pro vyhledávání: '"Crowd Counting"'
Publikováno v:
Complex & Intelligent Systems, Vol 10, Iss 4, Pp 5049-5070 (2024)
Abstract The incorporation of thermal imaging data in RGB-T images has demonstrated its usefulness in cross-modal crowd counting by offering complementary information to RGB representations. Despite achieving satisfactory results in RGB-T crowd count
Externí odkaz:
https://doaj.org/article/d200d8eed704451fa255f86e2e3b0f93
Publikováno v:
IEEE Access, Vol 12, Pp 131148-131163 (2024)
In this paper, we propose a novel and enhanced approach for crowd counting within the domain of manatee monitoring, aiming to significantly improve efficiency and accuracy. The proposed model achieves state-of-the-art results in the challenging task
Externí odkaz:
https://doaj.org/article/81cdef3b451e4988a824bd304100dc82
Autor:
Jihye Ryu, Kwangho Song
Publikováno v:
IEEE Access, Vol 12, Pp 68160-68170 (2024)
Recent work in crowd counting focuses on counting over detected individuals rather than estimating the number of people in the image. However, existing crowd localization methods directly detect the head point or region of individuals, which may enta
Externí odkaz:
https://doaj.org/article/f3c238bfc00f446b825f5fb350b0d7e4
Publikováno v:
IEEE Access, Vol 12, Pp 12818-12826 (2024)
Accurately measuring the level of crowding in transit cars is crucial for ensuring passenger safety and efficient operation. However, applying object detection algorithms to crowd counting in transit cars poses difficulties due to the low viewpoint o
Externí odkaz:
https://doaj.org/article/5bd0b1324956483f9f2db3f1c4cc2f1b
Publikováno v:
Frontiers in Neurorobotics, Vol 18 (2024)
IntroductionAccurately counting the number of dense objects in an image, such as pedestrians or vehicles, is a challenging and practical task. The existing density map regression methods based on CNN are mainly used to count a class of dense objects
Externí odkaz:
https://doaj.org/article/6682b2e87f9f4adf8cfb2869f2927624
Publikováno v:
EURASIP Journal on Wireless Communications and Networking, Vol 2023, Iss 1, Pp 1-26 (2023)
Abstract Passive crowd counting using channel state information (CSI) is a promising technology for applications in fields such as smart cities and commerce. However, the most existing algorithms can only recognize the total number of people in the m
Externí odkaz:
https://doaj.org/article/9b6a17ef7b784d48a8ed88384c56a6b3
Publikováno v:
Information, Vol 15, Iss 5, p 275 (2024)
Automated crowd counting is a crucial aspect of surveillance, especially in the context of mass events attended by large populations. Traditional methods of manually counting the people attending an event are error-prone, necessitating the developmen
Externí odkaz:
https://doaj.org/article/56f312c9f4af411baff343cd17a17070
Publikováno v:
Mathematics, Vol 12, Iss 10, p 1562 (2024)
Prevailing crowd counting approaches primarily rely on density map regression methods. Despite wonderful progress, significant scale variations and complex background interference within the same image remain challenges. To address these issues, in t
Externí odkaz:
https://doaj.org/article/fd84dbf92c4d46349bc24a8eb3b7d047
Publikováno v:
Computational Visual Media, Vol 9, Iss 4, Pp 859-873 (2023)
Abstract Crowd counting provides an important foundation for public security and urban management. Due to the existence of small targets and large density variations in crowd images, crowd counting is a challenging task. Mainstream methods usually ap
Externí odkaz:
https://doaj.org/article/2a82b860fcf948dda83e55ffb312c061
Autor:
ZHANG Yi, WU Qin
Publikováno v:
Jisuanji kexue, Vol 50, Iss 3, Pp 246-253 (2023)
Crowd counting aims to estimate the total number of people in an image and present its distribution accurately.The images in the relevant datasets usually involve a variety of scenes and include multiple people.To save labor,most datasets usually ann
Externí odkaz:
https://doaj.org/article/0bd3db80c583425681d818d0fb2cb01e