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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Adversarial Learning for Multiscale Crowd Counting Under Complex Scenes
Yuan Zhou, Jianxing Yang, Hongru Li, et al.
IEEE Transactions on Cybernetics (2020) Vol. 51, Iss. 11, pp. 5423-5432
Closed Access | Times Cited: 39

Showing 1-25 of 39 citing articles:

Rethinking Spatial Invariance of Convolutional Networks for Object Counting
Zhi-Qi Cheng, Qi Dai, Hong Li, et al.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2022), pp. 19606-19616
Open Access | Times Cited: 87
Video surveillance using deep transfer learning and deep domain adaptation: Towards better generalization
Yassine Himeur, Somaya Al‐Maadeed, Hamza Kheddar, et al.
Engineering Applications of Artificial Intelligence (2022) Vol. 119, pp. 105698-105698
Open Access | Times Cited: 73
Advancing 3D point cloud understanding through deep transfer learning: A comprehensive survey
Shahab Saquib Sohail, Yassine Himeur, Hamza Kheddar, et al.
Information Fusion (2024) Vol. 113, pp. 102601-102601
Open Access | Times Cited: 15
Feature-Aware Adaptation and Density Alignment for Crowd Counting in Video Surveillance
Junyu Gao, Yuan Yuan, Qi Wang
IEEE Transactions on Cybernetics (2020) Vol. 51, Iss. 10, pp. 4822-4833
Open Access | Times Cited: 75
Audio–visual representation learning for anomaly events detection in crowds
Junyu Gao, Hao Yang, Maoguo Gong, et al.
Neurocomputing (2024) Vol. 582, pp. 127489-127489
Open Access | Times Cited: 5
Object detection and crowd analysis using deep learning techniques: Comprehensive review and future directions
B. Ganga, Lata B.T., Venugopal K.R.
Neurocomputing (2024) Vol. 597, pp. 127932-127932
Closed Access | Times Cited: 5
Underwater Image Enhancement via Physical-Feedback Adversarial Transfer Learning
Yuan Zhou, Kangming Yan, Xiaofeng Li
IEEE Journal of Oceanic Engineering (2021) Vol. 47, Iss. 1, pp. 76-87
Closed Access | Times Cited: 37
A Novel cascaded deep architecture with weak-supervision for video crowd counting and density estimation
Santosh Kumar Tripathy, Subodh Srivastava, Divij Bajaj, et al.
Soft Computing (2024) Vol. 28, Iss. 13-14, pp. 8319-8335
Closed Access | Times Cited: 4
Crowd emotion evaluation based on fuzzy inference of arousal and valence
Xuguang Zhang, Xiuxin Yang, Weiguang Zhang, et al.
Neurocomputing (2021) Vol. 445, pp. 194-205
Open Access | Times Cited: 30
Deep learning in crowd counting: A survey
Lijia Deng, Qinghua Zhou, Shuihua Wang‎, et al.
CAAI Transactions on Intelligence Technology (2023) Vol. 9, Iss. 5, pp. 1043-1077
Open Access | Times Cited: 12
Density-Aware Curriculum Learning for Crowd Counting
Qi Wang, Wei Lin, Junyu Gao, et al.
IEEE Transactions on Cybernetics (2020) Vol. 52, Iss. 6, pp. 4675-4687
Closed Access | Times Cited: 21
Learning a deep network with cross-hierarchy aggregation for crowd counting
Qiang Guo, Xin Zeng, Shizhe Hu, et al.
Knowledge-Based Systems (2020) Vol. 213, pp. 106691-106691
Closed Access | Times Cited: 21
Single Convolutional Neural Network With Three Layers Model for Crowd Density Estimation
Adal A. Alashban, Alhanouf Alsadan, Norah Fahd Alhussainan, et al.
IEEE Access (2022) Vol. 10, pp. 63823-63833
Open Access | Times Cited: 13
Multi-scale Attention Recalibration Network for crowd counting
Jinyang Xie, Chen Pang, Zheng Yan-jun, et al.
Applied Soft Computing (2022) Vol. 117, pp. 108457-108457
Closed Access | Times Cited: 12
MetaUSACC: Unlabeled scene adaptation for crowd counting via meta-auxiliary learning
Chaoqun Ma, Jia Zeng, Penghui Shao, et al.
Expert Systems with Applications (2024) Vol. 247, pp. 123228-123228
Closed Access | Times Cited: 2
Congested Crowd Counting via Adaptive Multi-Scale Context Learning
Yani Zhang, Huailin Zhao, Zuodong Duan, et al.
Sensors (2021) Vol. 21, Iss. 11, pp. 3777-3777
Open Access | Times Cited: 14
AMS-CNN: Attentive multi-stream CNN for video-based crowd counting
Santosh Kumar Tripathy, Rajeev Srivastava
International Journal of Multimedia Information Retrieval (2021) Vol. 10, Iss. 4, pp. 239-254
Closed Access | Times Cited: 13
Searching Towards Class-Aware Generators for Conditional Generative Adversarial Networks
Peng Zhou, Lingxi Xie, Bingbing Ni, et al.
IEEE Signal Processing Letters (2022) Vol. 29, pp. 1669-1673
Open Access | Times Cited: 8
An Automatic Control Perspective on Parameterizing Generative Adversarial Network
Jinzhen Mu, Ming Xin, Shuang Li, et al.
IEEE Transactions on Cybernetics (2023) Vol. 54, Iss. 3, pp. 1854-1867
Closed Access | Times Cited: 4
Domain Adaptive Adversarial Learning Based on Physics Model Feedback for Underwater Image Enhancement
Yuan Zhou, Kangming Yan
arXiv (Cornell University) (2020)
Open Access | Times Cited: 12
MGSNet: A multi-scale and gated spatial attention network for crowd counting
Ying Shi, Jun Sang, Zhongyuan Wu, et al.
Applied Intelligence (2022) Vol. 52, Iss. 13, pp. 15436-15446
Closed Access | Times Cited: 7
SRNet: Scale-Aware Representation Learning Network for Dense Crowd Counting
Liangjun Huang, Luning Zhu, Shihui Shen, et al.
IEEE Access (2021) Vol. 9, pp. 136032-136044
Open Access | Times Cited: 10
CNN-based Single Image Crowd Counting: Network Design, Loss Function and Supervisory Signal.
Haoyue Bai, S.-H. Gary Chan
arXiv (Cornell University) (2020)
Closed Access | Times Cited: 8
Transportation Object Counting With Graph-Based Adaptive Auxiliary Learning
Yanda Meng, Joshua Bridge, Yitian Zhao, et al.
IEEE Transactions on Intelligent Transportation Systems (2022) Vol. 24, Iss. 3, pp. 3422-3437
Closed Access | Times Cited: 5
Multi-Scale Guided Attention Network for Crowd Counting
Pengfei Li, Min Zhang, Jian Wan, et al.
Scientific Programming (2021) Vol. 2021, pp. 1-13
Open Access | Times Cited: 6
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