Manning Wang

7.0k citations
124 papers · 1.7k indexed · h-index 22

Impact in

Papers in

Manning Wang

112 papers receiving 1.7k citations

Peers

Manning Wang
Comparison fields: 5 of 139
  • Computer Vision and Pattern Recognition 645
  • Geology 165
  • Media Technology 179
  • Radiology, Nuclear Medicine and Imaging 378
  • Health Informatics 19
Replace Jingfan Fan with:
Jingfan Fan China
Chaoyi Zhang Australia
Jun Cheng China
Simon Jégou France
Miao Liao China
Olof Enqvist Sweden
Jian Zheng China
Xin Cao China
Guanyu Yang China
Yi Xiao China
Manning Wang relative to Jingfan Fan China Jingfan Fan's profile →
Citations per field
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Citations per year

Countries citing papers authored by Manning Wang

Since Specialization
Citations

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

Fields of papers citing papers by Manning Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Manning Wang, 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 Manning Wang Line = papers co-authored together Manning Wang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 124 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2021162
2 2022112
3 202187
4 201380
5 202169
6 201954
7 202249
8 201441
9 202240
10 201940
11 201840
12 201638
13 201338
14 202435
15 202234
16 201828
17 200827
18 202227
19 202224
20 201823

About Manning Wang

Manning Wang is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering, Geology, Media Technology and Radiology, Nuclear Medicine and Imaging, having authored 124 papers that have together received 1.7k indexed citations. Recurring topics across this work include Robotics and Sensor-Based Localization (30 papers), Medical Image Segmentation Techniques (22 papers), 3D Shape Modeling and Analysis (12 papers), AI in cancer detection (11 papers), Augmented Reality Applications (11 papers), Radiomics and Machine Learning in Medical Imaging (10 papers), Domain Adaptation and Few-Shot Learning (10 papers) and Advanced Neural Network Applications (9 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (645 citations), Geology (165 citations), Media Technology (179 citations), Radiology, Nuclear Medicine and Imaging (378 citations) and Health Informatics (19 citations). Manning Wang has collaborated with scholars based in China, Germany and Taiwan. Frequent co-authors include Zhijian Song, Shaolei Liu, Linhao Qu, Kexue Fu, Zhijian Song, Yifeng Fan, Dongsheng Jiang, Weiwei Deng, Yinlong Liu and Qiuye Jin. Their work appears in journals such as Medical Physics, IEEE Access, Frontiers of Computer Science, Expert Systems with Applications and Briefings in Bioinformatics.

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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