John Wang

31 papers receiving 829 citations

Hit Papers

AprilTag 2: Efficient and robust fiducial detection 2016 · 526 citations
5262016202620192022100200300400500

Peers

John Wang
Comparison fields: 5 of 120
  • Computer Vision and Pattern Recognition 389
  • Health Informatics 20
  • Aerospace Engineering 284
  • Geology 52
  • Human-Computer Interaction 32
Replace Francesco Amigoni with:
Francesco Amigoni Italy
Gigel Măceșanu Romania
Edward Tunstel United States
Jiasi Chen United States
Xukan Ran United States
Shaoshan Liu United States
Yiming Miao China
Ni Zhang China
Yue Ming China
Tiberiu Cocias Romania
John Wang relative to Francesco Amigoni Italy Francesco Amigoni's profile →
Citations per field
00.5×1.5×2.5×
Francesco Amigoni · 1×
Citations per year

Countries citing papers authored by John Wang

Since Specialization
Citations

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

Fields of papers citing papers by John Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 33 papers — load more, or switch the sort, to bring in the rest.

#Work
1
AprilTag 2: Efficient and robust fiducial detection
Hit paper breakdown →
2016526
2 200563
3 199462
4 200360
5 201822
6 202320
7 199419
8 200819
9 202413
10 200810
11
Navigating large-scale semi-structured data in business portals
20019
12 20088
13 20108
14 20107
15 20136
16 20205
17 20105
18 20104
19 20074
20
ZL Technologies at TREC 2009 Legal Interactive Comparing Exclusionary and Investigative Approaches for Electronic Discovery using the TREC Enron Corpus
20093

About John Wang

John Wang is a scholar working on Artificial Intelligence, Information Systems, Computer Vision and Pattern Recognition, Computer Networks and Communications and Management Information Systems, having authored 33 papers that have together received 893 indexed citations. Recurring topics across this work include Data Mining Algorithms and Applications (5 papers), Topic Modeling (5 papers), Face and Expression Recognition (4 papers), Big Data and Business Intelligence (4 papers), Advanced Vision and Imaging (3 papers), Data Quality and Management (3 papers), Neural Networks and Applications (2 papers) and Sentiment Analysis and Opinion Mining (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (389 citations), Health Informatics (20 citations), Aerospace Engineering (284 citations), Geology (52 citations) and Human-Computer Interaction (32 citations). John Wang has collaborated with scholars based in United States, India and Thailand. Frequent co-authors include Edwin Olson, Edward H. Adelson, Lisa Shieh, Amit Saxena, Dan Zhu, Huanyu Ouyang, Xiaohua Hu, Chandana Chakraborty, Gavin Brown and Xiao Wang. Their work appears in journals such as SAE technical papers on CD-ROM/SAE technical paper series, International Journal of Data Warehousing and Mining, International Journal of Human Capital and Information Technology Professionals, Journal of the American Medical Informatics Association and International Journal of Data Mining Modelling and Management.

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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