Ming Zeng

2.6k total citations · 1 hit paper
57 papers, 1.6k citations indexed

About

Ming Zeng is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Signal Processing. According to data from OpenAlex, Ming Zeng has authored 57 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 44 papers in Computer Vision and Pattern Recognition, 16 papers in Artificial Intelligence and 5 papers in Signal Processing. Recurrent topics in Ming Zeng's work include Face recognition and analysis (11 papers), Human Pose and Action Recognition (11 papers) and Anomaly Detection Techniques and Applications (9 papers). Ming Zeng is often cited by papers focused on Face recognition and analysis (11 papers), Human Pose and Action Recognition (11 papers) and Anomaly Detection Techniques and Applications (9 papers). Ming Zeng collaborates with scholars based in China, United States and Norway. Ming Zeng's co-authors include Le T. Nguyen, Joy Zhang, Ole J. Mengshoel, Pang Wu, Bo Yu, Jiang Zhu, Fang Wen, Yinglin Zheng, Dong Chen and Jianmin Bao and has published in prestigious journals such as Polymer, Sensors and Information Sciences.

In The Last Decade

Ming Zeng

50 papers receiving 1.5k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Convolutional Neural Networks for Human Activity Recognition using Mobile Sensors

2014 607 citations Ming Zeng, Le T. Nguyen et al. profile →

Peers

Ming Zeng

CVPR

AI

BE

SP

CNC

Syed Mohsen Naqvi United Kingdom

Ran Xu China

Dimitrios Kosmopoulos Greece

Tsung‐Han Tsai Taiwan

Hakan Bilen United Kingdom

Shaharyar Kamal South Korea

Wenhan Hu China

Shuji Hao Singapore

Maheshkumar H. Kolekar India

Sergey Tulyakov United States

Syed Mohsen Naqvi United Kingdom

Ming Zeng

831 ×0.7

CVPR

664 ×1.5

AI

345 ×1.4

BE

511 ×2.6

SP

136 ×0.7

CNC

Citations per year, relative to Ming Zeng Ming Zeng (= 1×) peers Syed Mohsen Naqvi

Countries citing papers authored by Ming Zeng

Since Specialization

Citations

This map shows the geographic impact of Ming Zeng's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Ming Zeng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ming Zeng more than expected).

Fields of papers citing papers by Ming Zeng

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ming Zeng. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Ming Zeng. The network helps show where Ming Zeng may publish in the future.

Co-authorship network of co-authors of Ming Zeng

This figure shows the co-authorship network connecting the top 25 collaborators of Ming Zeng. A scholar is included among the top collaborators of Ming Zeng based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Ming Zeng. Ming Zeng is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Zhang, Bingbo, Xueqing Li, Ming Zeng, & Jingguo Cao. (2025). COMFO: Integrated deep learning model facilitates discovery of multifunctional polyimide materials. Polymer. 320. 128081–128081. 2 indexed citations

2.

Zhang, Bo, et al.. (2024). Multi-property prediction and high-throughput screening of polyimides: An application case for interpretable machine learning. Polymer. 312. 127603–127603. 3 indexed citations

3.

Chen, Jianpeng, Yujing Wang, Ming Zeng, et al.. (2024). Customizing graph neural networks using path reweighting. Information Sciences. 674. 120681–120681. 2 indexed citations

4.

Wu, Zizhao, et al.. (2024). SPAC-Net: Rethinking Point Cloud Completion With Structural Prior. IEEE Transactions on Visualization and Computer Graphics. 31(9). 6268–6279.

5.

Zeng, Ming. (2023). The classification of red wine quality based on machine learning techniques. UA Campus Repository (The University of Arizona). 133–133. 1 indexed citations

6.

Zheng, Yinglin, et al.. (2023). EMEF: Ensemble Multi-Exposure Image Fusion. Proceedings of the AAAI Conference on Artificial Intelligence. 37(2). 1710–1718. 6 indexed citations

7.

Liu, Pengfei, et al.. (2023). MusicFace: Music-driven expressive singing face synthesis. Computational Visual Media. 10(1). 119–136. 7 indexed citations

8.

Zeng, Ming, et al.. (2022). SemNet: Learning semantic attributes for human activity recognition with deep belief networks. Frontiers in Big Data. 5. 879389–879389. 3 indexed citations

9.

Zeng, Ming, et al.. (2022). An Improved Object Detection Algorithm for Assembly Line Garbage Sorting. 2022 41st Chinese Control Conference (CCC). 7118–7123. 1 indexed citations

10.

Zeng, Ming, et al.. (2021). Controllable Facial Caricaturization With Localized Deformation and Personalized Semantic Attentions. IEEE Transactions on Multimedia. 24. 4041–4053. 1 indexed citations

11.

Zhao, Yifan, et al.. (2021). FACIAL: Synthesizing Dynamic Talking Face with Implicit Attribute Learning. 2021 IEEE/CVF International Conference on Computer Vision (ICCV). 3847–3856. 90 indexed citations

12.

Li, Xu, et al.. (2020). Spatio-temporal Collaborative Convolution for Video Action Recognition. 554–558. 2 indexed citations

13.

Wu, Zizhao, Ming Zeng, Feiwei Qin, Yigang Wang, & Jiří Kosinka. (2019). Active 3-D Shape Cosegmentation With Graph Convolutional Networks. IEEE Computer Graphics and Applications. 39(2). 77–88. 5 indexed citations

14.

Kan, Shichao, et al.. (2017). SURF binarization and fast codebook construction for image retrieval. Journal of Visual Communication and Image Representation. 49. 104–114. 16 indexed citations

15.

Wei, Qingyang, Tianyu Ma, Ming Zeng, et al.. (2017). Crystal identification for a dual-layer-offset LYSO based PET system via Lu-176 background radiation and mean shift algorithm. Physics in Medicine and Biology. 63(2). 02NT01–02NT01. 6 indexed citations

16.

Cen, Yigang, et al.. (2017). Object tracking based on adaptive updating of a spatial-temporal context model. KSII Transactions on Internet and Information Systems. 11(11).

17.

Zeng, Ming, Le T. Nguyen, Bo Yu, et al.. (2014). Convolutional Neural Networks for Human Activity Recognition using Mobile Sensors. 607 indexed citations breakdown →

18.

Cheng, Xuan, Ming Zeng, & Xinguo Liu. (2013). Feature-preserving filtering with L0 gradient minimization. Computers & Graphics. 38. 150–157. 46 indexed citations

19.

Zeng, Ming, et al.. (2012). Octree-based fusion for realtime 3D reconstruction. Graphical Models. 75(3). 126–136. 83 indexed citations

20.

Zeng, Ming, et al.. (2006). Color Segmentation of Nuclei of Blood Cell Using Support Vector Machines. Journal of Optoelectronics·laser. 2 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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