Results 51 to 60 of about 124,762 (273)
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
Crowd Counting Through Walls Using WiFi
, 2017 Counting the number of people inside a building, from outside and without entering the building, is crucial for many applications. In this paper, we are interested in counting the total number of people walking inside a building (or in general behind ...
Depatla, Saandeep, Mostofi, Yasamin
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On the Complexity of Mining Itemsets from the Crowd Using Taxonomies [PDF]
, 2013 We study the problem of frequent itemset mining in domains where data is not recorded in a conventional database but only exists in human knowledge. We provide examples of such scenarios, and present a crowdsourcing model for them.
Amarilli, Antoine +2 more
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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
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People, Penguins and Petri Dishes: Adapting Object Counting Models To New Visual Domains And Object Types Without Forgetting [PDF]
, 2017 In this paper we propose a technique to adapt a convolutional neural network (CNN) based object counter to additional visual domains and object types while still preserving the original counting function.
Keogh, Ciara E. +4 more
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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
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Spatiotemporal Modeling for Crowd Counting in Videos
, 2017 Region of Interest (ROI) crowd counting can be formulated as a regression problem of learning a mapping from an image or a video frame to a crowd density map.
Shi, Xingjian +2 more
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Counting with Focus for Free [PDF]
, 2019 This paper aims to count arbitrary objects in images. The leading counting approaches start from point annotations per object from which they construct density maps.
Mettes, Pascal +2 more
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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
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Weighing Counts: Sequential Crowd Counting by Reinforcement Learning [PDF]
, 2020 We formulate counting as a sequential decision problem and present a novel crowd counting model solvable by deep reinforcement learning. In contrast to existing counting models that directly output count values, we divide one-step estimation into a sequence of much easier and more tractable sub-decision problems.
Liu, Liang +5 more
openaire +2 more sources