Results 31 to 40 of about 124,762 (273)
Texture features-based lightweight passive multi-state crowd counting algorithm
EURASIP Journal on Wireless Communications and Networking, 2023 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 monitoring ...
Yong Tian +5 more
doaj +1 more source
Shallow feature based dense attention network for crowd counting [PDF]
, 2020 While the performance of crowd counting via deep learning has been improved dramatically in the recent years, it remains an ingrained problem due to cluttered backgrounds and varying scales of people within an image.
Ding, Guiguang +3 more
core +2 more sources
Iterative Crowd Counting [PDF]
, 2018 ECCV ...
Ranjan, Viresh, Le, Hieu, Hoai, Minh
openaire +2 more sources
Scene Invariant Crowd Counting [PDF]
2011 International Conference on Digital Image Computing: Techniques and Applications, 2011 This paper describes a scene invariant crowd counting algorithm that uses local features to monitor crowd size. Unlike previous algorithms that require each camera to be trained separately, the proposed method uses camera calibration to scale between viewpoints, allowing a system to be trained and tested on different scenes.
Ryan, David +3 more
openaire +2 more sources
Exploiting Unlabeled Data in CNNs by Self-supervised Learning to Rank [PDF]
, 2019 For many applications the collection of labeled data is expensive laborious. Exploitation of unlabeled data during training is thus a long pursued objective of machine learning.
Bagdanov, Andrew D. +2 more
core +2 more sources
DTCC: Multi-level dilated convolution with transformer for weakly-supervised crowd counting
Computational Visual Media, 2023 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.
Zhuangzhuang Miao +4 more
doaj +1 more source
Crowd Science and Crowd Counting [PDF]
Impact, 2019 ESTIMATING CROWD SIZE, both a priori and in real-time, is an essential element for planning, and maintaining, crowd safety in places of public assembly.
openaire +1 more source
IEEE Access, 2019 This paper proposes an automatic scale-adaptive approach with attention mechanism-based crowd spatial information addressing the crowd counting task, i.e. a novel cascaded crowd counting network.
Weihang Kong +3 more
doaj +1 more source
ResnetCrowd: a residual deep learning architecture for crowd counting, violent behaviour detection and crowd density level classification [PDF]
, 2017 In this paper we propose ResnetCrowd, a deep residual architecture for simultaneous crowd counting, violent behaviour detection and crowd density level classification.
Little, Suzanne +3 more
core +1 more source
Wi-CaL: WiFi Sensing and Machine Learning Based Device-Free Crowd Counting and Localization
IEEE Access, 2022 Wireless sensing represented by WiFi channel state information (CSI) is now enabling various fields of applications such as person identification, human activity recognition, occupancy detection, localization, and crowd estimation these days.
Hyuckjin Choi +4 more
doaj +1 more source