Results 51 to 60 of about 322,190 (190)
Crowd Counting Algorithm Based on Scale Adaptive Convolutional Neural Network [PDF]
Jisuanji gongcheng, 2020 In order to solve the problem of crowd occlusion and scale change in a single image,this paper proposes a crowd counting algorithm based on multi-column convolution neural network.The algorithm uses Convolutional Neural Network(CNN) with receptive fields
ZHAI Qiang, WANG Luyang, YIN Baoqun, PENG Sifan, XING Sisi
doaj +1 more source
German crowd-investing platforms: Literature review and survey [PDF]
, 2016 This article presents a comprehensive overview of the current German crowd-investing market drawing on a data-set of 31 crowd-investing platforms including the analysis of 265 completed projects. While crowd-investing market still only represents a niche
David Grundy +3 more
core +1 more source
CC-DETR: DETR with Hybrid Context and Multi-Scale Coordinate Convolution for Crowd Counting
MathematicsPrevailing 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.
Yanhong Gu +3 more
doaj +1 more source
CoRROcclusion is one of the fundamental challenges in crowd counting. In the community, various data-driven approaches have been developed to address this issue, yet their effectiveness is limited. This is mainly because most existing crowd counting datasets on which the methods are trained are based on passive cameras, restricting their ability to fully ...
Runling Long +7 more
openaire +3 more sources
AAFM: Adaptive Attention Fusion Mechanism for Crowd Counting
IEEE Access, 2020 CNN-based crowd counting methods have achieved great progress in recent years. However, most of these CNN-based crowd counting methods do not make full use of contextual information, which contains high-level semantic features and low-level detail ...
Zuodong Duan, Huimin Chen, Jiahao Deng
doaj +1 more source
Scene adaptive crowd counting [PDF]
, 2020 We consider the problem of scene adaptive crowd counting. Given a target camera scene, our goal is to adapt a model to this specific scene with only a few labeled/unlabeled images.
Krishna Reddy, Mahesh Kumar
core
Coordinated crowd simulation with topological scene analysis [PDF]
, 2016 This paper proposes a new algorithm to produce globally coordinated crowds in an environment with multiple paths and obstacles. Simple greedy crowd control methods easily lead to congestion at bottlenecks within scenes, as the characters do not cooperate
Taku Komura +6 more
core +1 more source
Fine-grained Domain Adaptive Crowd Counting via Point-derived Segmentation [PDF]
, 2023 Due to domain shift, a large performance drop is usually observed when a trained crowd counting model is deployed in the wild. While existing domain-adaptive crowd counting methods achieve promising results, they typically regard each crowd image as a ...
Ren, Sucheng +5 more
core +3 more sources
Cascaded Multi-Task Learning of Head Segmentation and Density Regression for RGBD Crowd Counting
IEEE Access, 2020 In this paper we propose a novel regression based RGBD crowd counting method. Compared with previous RGBD crowd counting methods which mainly exploit depth cue to facilitate person/head detection, our approach adopts density map regression and is more ...
Desen Zhou, Qian He
doaj +1 more source
Depth Information Guided Crowd Counting for complex crowd scenes [PDF]
Pattern Recognition Letters, 2019 9 pages, 8 figures.
Mingliang Xu 0001 +6 more
openaire +3 more sources