Results 221 to 230 of about 40,421 (274)

InCrowd-VI: A Realistic Visual-Inertial Dataset for Evaluating Simultaneous Localization and Mapping in Indoor Pedestrian-Rich Spaces for Human Navigation. [PDF]

Sensors (Basel)
Bamdad M, Hutter HP, Darvishy A.
europepmc   +1 more source

Interpretable and lightweight fall detection in a heritage gallery using YOLOv11-SEFA for edge deployment. [PDF]

Sci Rep
Wu S, Yang H, Hu Y, Ji X, Cheng S.
europepmc   +1 more source

MRSNet: Multi-Resolution Scale Feature Fusion-Based Universal Density Counting Network. [PDF]

Sensors (Basel)
Zhang Y, Song W, Shao M, Liu X.
europepmc   +1 more source

The Citizens Protein Project 2: The first publicly crowd-funded observational study on exhaustive analysis of popular whey protein supplements in India reveal poor quality and deceptive marketing claims of medical pharmaceutical- compared to nutraceutical- industry powders. [PDF]

Medicine (Baltimore)
Philips CA, Theruvath AH, Sreemohan A, Baby A, Jose S, Philips M, Philip T, members of the Mission for Ethics and Science in Healthcare (MESH).   +7 more
europepmc   +1 more source

A Robust Framework Fusing Visual SLAM and 3D Gaussian Splatting with a Coarse-Fine Method for Dynamic Region Segmentation. [PDF]

Sensors (Basel)
Chen Z, Hu Y, Liu Y.
europepmc   +1 more source

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Granular-based dense crowd density estimation

Multimedia Tools and Applications, 2017
Dense crowd density estimation is one of the fundamental tasks in crowd analysis. While tremendous progress has been made to understand crowd scenes along with the rise of Convolutional Neural Networks (CNNs), research work on dense crowd density estimation is still an ongoing process.
Ven Jyn Kok, Chee Seng Chan
exaly   +3 more sources

Fast crowd density estimation with convolutional neural networks

Engineering Applications of Artificial Intelligence, 2015
As an effective way for crowd control and management, crowd density estimation is an important research topic in artificial intelligence applications. Since the existing methods are hard to satisfy the accuracy and speed requirements of engineering applications, we propose to estimate crowd density by an optimized convolutional neural network (ConvNet).
Mao Ye, Ce Zhu
exaly   +2 more sources

Density estimation in crowd videos

2014 22nd Signal Processing and Communications Applications Conference (SIU), 2014
In crowd surveillance systems, it is important to select the proper analysis algorithm considering the properties of the video content. The inappropriate algorithm selection may result in performance degradation and generation of false alarms. An important feature of crowd videos is the density of the crowd.
Ayse Elvan Gunduz, Tugba Taskaya Temizel, Alptekin Temizel   +2 more
openaire   +1 more source

Crowd density estimation: An improved approach

IEEE 10th INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING PROCEEDINGS, 2010
Crowd density estimation is important in crowd analysis and texture analysis is an efficient method to estimate crowd density, this paper proposes an improved estimation approach based on texture analysis. First, background is removed by using a combination of optical flow and background subtract method. Then according to texture analysis, a set of new
Wei Li, Xiaojuan Wu, Koichi Matsumoto, Hua-An Zhao   +3 more
openaire   +1 more source