Mao Ye

9.9k total citations · 3 hit papers
318 papers, 6.0k citations indexed

About

Mao Ye is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, Mao Ye has authored 318 papers receiving a total of 6.0k indexed citations (citations by other indexed papers that have themselves been cited), including 173 papers in Computer Vision and Pattern Recognition, 90 papers in Artificial Intelligence and 39 papers in Computer Networks and Communications. Recurrent topics in Mao Ye's work include Video Surveillance and Tracking Methods (36 papers), Domain Adaptation and Few-Shot Learning (36 papers) and Advanced Neural Network Applications (32 papers). Mao Ye is often cited by papers focused on Video Surveillance and Tracking Methods (36 papers), Domain Adaptation and Few-Shot Learning (36 papers) and Advanced Neural Network Applications (32 papers). Mao Ye collaborates with scholars based in China, United States and Australia. Mao Ye's co-authors include Wang-Chien Lee, Dik Lun Lee, Peifeng Yin, Juan Wu, Guihai Chen, Qihe Liu, Xiatian Zhu, Xue Li, Jie Wu and Xingjie Liu and has published in prestigious journals such as Journal of Financial Economics, IEEE Transactions on Pattern Analysis and Machine Intelligence and Review of Financial Studies.

In The Last Decade

Mao Ye

277 papers receiving 5.6k 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.

Exploiting geographical influence for collaborative point-of-interest recommendation

2011 793 citations Mao Ye et al. profile →
EECS: an energy efficient clustering scheme in wireless sensor networks

2005 616 citations Mao Ye et al. profile →
An unequal cluster-based routing protocol in wireless sensor networks

2007 373 citations Mao Ye et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Mao Ye China	33	2.1k	1.6k	1.4k	1.1k	852	318	6.0k
Huadóng Ma China	46	3.0k 1.4×	3.4k 2.1×	1.7k 1.2×	2.4k 2.2×	640 0.8×	516	9.2k
Zhikui Chen China	37	1.3k 0.6×	1.5k 1.0×	2.1k 1.6×	896 0.8×	890 1.0×	199	5.3k
Zhibo Wang China	42	803 0.4×	1.7k 1.1×	2.7k 2.0×	1.8k 1.6×	994 1.2×	274	6.7k
Bo Liu China	34	1.1k 0.5×	1.3k 0.8×	1.5k 1.1×	988 0.9×	598 0.7×	408	4.6k
Sung‐Bae Cho South Korea	36	1.8k 0.9×	1.1k 0.7×	2.4k 1.7×	443 0.4×	486 0.6×	320	5.4k
Wenzhong Guo China	39	1.4k 0.7×	1.4k 0.9×	1.9k 1.4×	1.2k 1.1×	872 1.0×	271	5.3k
Pan Zhou China	47	3.5k 1.7×	2.6k 1.7×	2.6k 1.9×	1.3k 1.2×	1.1k 1.3×	337	9.6k
Victor S. Sheng United States	41	1.9k 0.9×	822 0.5×	4.5k 3.3×	501 0.5×	2.1k 2.5×	304	8.0k
Gwanggil Jeon South Korea	46	3.4k 1.6×	1.8k 1.1×	1.7k 1.2×	1.3k 1.2×	1.2k 1.4×	533	8.8k
S. S. Iyengar United States	31	1.1k 0.5×	1.8k 1.1×	1.5k 1.1×	1.1k 1.1×	700 0.8×	217	5.1k

Countries citing papers authored by Mao Ye

Since Specialization

Citations

This map shows the geographic impact of Mao Ye'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 Mao Ye with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mao Ye more than expected).

Fields of papers citing papers by Mao Ye

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mao Ye. 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 Mao Ye. The network helps show where Mao Ye may publish in the future.

Co-authorship network of co-authors of Mao Ye

This figure shows the co-authorship network connecting the top 25 collaborators of Mao Ye. A scholar is included among the top collaborators of Mao Ye 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 Mao Ye. Mao Ye 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.

Ye, Mao, et al.. (2025). Time-series forest age estimation in Xinjiang based on forest disturbance and recovery detection. Ecological Indicators. 170. 113043–113043. 1 indexed citations

2.

Liu, Dan, Qing Xia, Fanrong Meng, Mao Ye, & Jianwei Zhang. (2025). Multi-level semantic-assisted prototype learning for Few-Shot Action Recognition. Neurocomputing. 636. 130022–130022.

3.

Chen, Shengjia, et al.. (2025). Language-Driven Motion Prior Knowledge Learning for Moving Infrared Small Target Detection. IEEE Transactions on Geoscience and Remote Sensing. 63. 1–14.

4.

Jian, Yue, et al.. (2025). ODE-based generative modeling: Learning from a single natural image. Expert Systems with Applications. 276. 127185–127185.

5.

Liu, Dan, Fanrong Meng, Qing Xia, et al.. (2024). Temporal cues enhanced multimodal learning for action recognition in RGB-D videos. Neurocomputing. 594. 127882–127882. 10 indexed citations

6.

Ye, Mao, et al.. (2024). Shooting condition insensitive unmanned aerial vehicle object detection. Expert Systems with Applications. 246. 123221–123221. 8 indexed citations

7.

Gan, Yan, et al.. (2024). SPGAN: Siamese projection Generative Adversarial Networks. Knowledge-Based Systems. 285. 111353–111353. 8 indexed citations

8.

Liu, Wei, Mao Ye, Luping Ji, et al.. (2024). Multi-Level Alignments for Compressed Video Super-Resolution. IEEE Transactions on Consumer Electronics. 70(3). 5101–5114. 1 indexed citations

9.

Ye, Mao, et al.. (2024). Multi-Reference-Based Cross-Scale Feature Fusion for Compressed Video Super Resolution. IEEE Transactions on Broadcasting. 70(3). 895–908. 6 indexed citations

10.

Chen, Shengjia, et al.. (2024). SSTNet: Sliced Spatio-Temporal Network With Cross-Slice ConvLSTM for Moving Infrared Dim-Small Target Detection. IEEE Transactions on Geoscience and Remote Sensing. 62. 1–12. 44 indexed citations

11.

Liu, Dan, et al.. (2023). Cross-domain video action recognition via adaptive gradual learning. Neurocomputing. 556. 126622–126622. 6 indexed citations

12.

Ye, Mao, et al.. (2023). 利用光轴可移动液晶透镜的立体图像采集系统. Acta Optica Sinica. 43(3). 311002–311002. 1 indexed citations

13.

Gan, Yan, Mao Ye, Dan Liu, & Yiguang Liu. (2023). Training generative adversarial networks by auxiliary adversarial example regulator. Applied Soft Computing. 136. 110086–110086. 3 indexed citations

14.

Ye, Mao, et al.. (2023). Mechanics Characteristics of a 3D Star-Shaped Negative Poisson’s Ratio Composite Structure. Materials. 16(11). 3950–3950. 20 indexed citations

15.

Ye, Mao, et al.. (2023). Source-free domain adaptation with Class Prototype Discovery. Pattern Recognition. 145. 109974–109974. 23 indexed citations

16.

Ye, Mao, et al.. (2023). Compressed-SDR to HDR Video Reconstruction. IEEE Transactions on Pattern Analysis and Machine Intelligence. 46(5). 3679–3691. 1 indexed citations

17.

Xiao, Haifeng, Zhiqiang Liu, Baolin Tan, & Mao Ye. (2022). A Depth Sensor Based on Transient Property of Liquid Crystal Lens. Photonic Sensors. 13(2). 2 indexed citations

18.

Zheng, Liming, Xiaoxi Chen, Yalei Zhang, & Mao Ye. (2021). Influence of the Maximum Blur Radius on Depth Sensor Based on Liquid Crystal Lens. Photonic Sensors. 11(3). 371–375. 1 indexed citations

19.

Ye, Mao, et al.. (2020). Improving person re-identification by attention and multi-attributes. Journal of Image and Graphics. 25(5). 936–945.

20.

Li, Xudong, Mao Ye, Yiguang Liu, & Ce Zhu. (2017). Adaptive Deep Convolutional Neural Networks for Scene-Specific Object Detection. IEEE Transactions on Circuits and Systems for Video Technology. 29(9). 2538–2551. 44 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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