Mengmeng Xu

1.2k citations
13 papers · 154 indexed · h-index 7

Mengmeng Xu

12 papers receiving 151 citations

Peers

Mengmeng Xu
Comparison fields: 5 of 46
  • Computer Vision and Pattern Recognition 117
  • Industrial and Manufacturing Engineering 33
  • Artificial Intelligence 52
  • Media Technology 14
  • Polymers and Plastics 21
Replace Csaba Domokos with:
Csaba Domokos Hungary
Sanyi Zhang China
Jiahao Wang China
Duowen Chen China
Angtian Wang United States
Jinrong Yang China
Mustafa Gökhan Uzunbaş United States
Míriam Bellver Spain
Ali Mohammad Pazandeh Iran
Renjiao Yi China
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Citations per year

Countries citing papers authored by Mengmeng Xu

Since Specialization
Citations

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

Fields of papers citing papers by Mengmeng Xu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Mengmeng Xu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Mengmeng Xu Line = papers co-authored together Mengmeng Xu links everyone, so they are left out of the graph.

All Works

13 of 13 papers shown
#Work
1 20242
2 20240
3 20233
4 20235
5
Low-Fidelity Video Encoder Optimization for Temporal Action Localization
202113
6 202132
7
Salient object detection based on conditional generative adversarial networks for video
20191
8
Missing Labels in Object Detection
201916
9
Semantic Part RCNN for Real-World Pedestrian Detection.
20193
10 201917
11 201517
12 201431
13 200414

About Mengmeng Xu

Mengmeng Xu is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design and Media Technology, having authored 13 papers that have together received 154 indexed citations. Recurring topics across this work include Human Pose and Action Recognition (4 papers), Advanced Image and Video Retrieval Techniques (3 papers), Advanced Neural Network Applications (3 papers), Video Surveillance and Tracking Methods (2 papers), Multimodal Machine Learning Applications (2 papers), Industrial Vision Systems and Defect Detection (2 papers), Domain Adaptation and Few-Shot Learning (2 papers) and Image Processing Techniques and Applications (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (117 citations), Industrial and Manufacturing Engineering (33 citations) and Artificial Intelligence (52 citations). Mengmeng Xu has collaborated with scholars based in China, Saudi Arabia and United Kingdom. Frequent co-authors include Bernard Ghanem, Junfeng Jing, Pengfei Li, Yancheng Bai, Brais Martínez, Xiatian Zhu, Qi Li, Paul M. Thompson, Arthur W. Toga and Tao Xiang. Their work appears in journals such as IEEE Transactions on Medical Imaging, Sensors and IEEE Transactions on Circuits and Systems for Video Technology.

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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