Zobrazeno 1 - 10
of 2 042
pro vyhledávání: '"crowd counting"'
Autor:
Zhongyuan Yuan
Publikováno v:
PeerJ Computer Science, Vol 10, p e2273 (2024)
Crowd counting aims to estimate the number and distribution of the population in crowded places, which is an important research direction in object counting. It is widely used in public place management, crowd behavior analysis, and other scenarios,
Externí odkaz:
https://doaj.org/article/f4062d3bdaeb417da4eca5cc9d8e0b0a
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
Autor:
Takehiro Habara, Ryosuke Kojima
Publikováno v:
IEEE Access, Vol 12, Pp 154888-154900 (2024)
Crowd counting and density estimation are the principal objectives of crowd analysis, which offer significant applications in surveillance, event management, and traffic design. In the field of crowd flow, including simulations, the dynamics of crowd
Externí odkaz:
https://doaj.org/article/623a0abebceb40aab3db8113c195bec6
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:
Applied Sciences, Vol 14, Iss 20, p 9386 (2024)
Dense urban environments pose significant challenges when it comes to detecting and measuring crowd size due to their nature of being free-flow environments containing many dynamic factors. In this paper, we use a wireless sensor network (WSN) to per
Externí odkaz:
https://doaj.org/article/8ce3c7e3b8d24b49bab3b0c0b95dea83
Publikováno v:
Sensors, Vol 24, Iss 18, p 5974 (2024)
This study focuses on the problem of dense object counting. In dense scenes, variations in object scales and uneven distributions greatly hinder counting accuracy. The current methods, whether CNNs with fixed convolutional kernel sizes or Transformer
Externí odkaz:
https://doaj.org/article/ac7b56c7b3ba430583d37c793004cfb5
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