Junhua Mao

5.3k citations
19 papers · 629 · h-index 13

Impact in

    • Multimodal Machine Learning Applications
    • Advanced Image and Video Retrieval Techniques
    • Human Pose and Action Recognition
    • Video Analysis and Summarization
  • Nephrology top 10%
    • Renal Diseases and Glomerulopathies
    • Chronic Kidney Disease and Diabetes

Papers in

Junhua Mao

19 papers receiving 615 citations

Peers

Junhua Mao
Comparison fields: 5 of 90
  • Computer Vision and Pattern Recognition 335
  • Nephrology 71
  • Artificial Intelligence 224
  • Pathology and Forensic Medicine 34
  • Human-Computer Interaction 9
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Citations per field
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Citations per year

Countries citing papers authored by Junhua Mao

Since Specialization
Citations

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

Fields of papers citing papers by Junhua Mao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

19 of 19 papers shown
#Work
1 2017124
2
Are You Talking to a Machine? Dataset and Methods for Multilingual Image Question
2015121
3 201373
4 201462
5
Are you talking to a machine? Dataset and methods for multilingual image question answering
201545
6 201342
7 202230
8 201925
9 201317
10
Learning From Weakly Supervised Data by The Expectation Loss SVM (e-SVM) algorithm
201416
11 202215
12 201414
13 201612
14 201410
15 202310
16 20187
17 20244
18 20001
19 20241

About Junhua Mao

Junhua Mao is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Molecular Biology, Nephrology and Physiology, having authored 19 papers that have together received 629 indexed citations. Recurring topics across this work include Domain Adaptation and Few-Shot Learning (5 papers), Multimodal Machine Learning Applications (4 papers), Advanced Image and Video Retrieval Techniques (4 papers), Human Pose and Action Recognition (3 papers), Thermochemical Biomass Conversion Processes (3 papers), Renal Diseases and Glomerulopathies (3 papers), Tuberous Sclerosis Complex Research (3 papers) and Advanced Neural Network Applications (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (335 citations), Nephrology (71 citations), Artificial Intelligence (224 citations), Pathology and Forensic Medicine (34 citations) and Human-Computer Interaction (9 citations). Junhua Mao has collaborated with scholars based in China, United States and Germany. Frequent co-authors include Alan Yuille, Chenxi Liu, Fei Sha, Haoyuan Gao, Wei Xu, Lei Wang, Jie Zhou, Zhiheng Huang, Lei Jiang and Junwei Yang. Their work appears in journals such as Fuel, Journal of Alloys and Compounds, Emergency Radiology, Powder Technology and Journal of the American Society of Nephrology.

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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