Hung‐Khoon Tan

969 total citations
35 papers, 656 citations indexed

About

Hung‐Khoon Tan is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, Hung‐Khoon Tan has authored 35 papers receiving a total of 656 indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Computer Vision and Pattern Recognition, 9 papers in Artificial Intelligence and 3 papers in Computer Networks and Communications. Recurrent topics in Hung‐Khoon Tan's work include Advanced Image and Video Retrieval Techniques (24 papers), Image Retrieval and Classification Techniques (13 papers) and Video Analysis and Summarization (11 papers). Hung‐Khoon Tan is often cited by papers focused on Advanced Image and Video Retrieval Techniques (24 papers), Image Retrieval and Classification Techniques (13 papers) and Video Analysis and Summarization (11 papers). Hung‐Khoon Tan collaborates with scholars based in Hong Kong, Malaysia and Singapore. Hung‐Khoon Tan's co-authors include Chong‐Wah Ngo, Xiao Wu, Tat‐Seng Chua, Wan‐Lei Zhao, Alexander G. Hauptmann, Richard S. Hong, Shuicheng Yan, Jinhui Tang, Richang Hong and Song Tan and has published in prestigious journals such as IEEE Access, Pattern Recognition and IEEE Transactions on Circuits and Systems for Video Technology.

In The Last Decade

Hung‐Khoon Tan

33 papers receiving 623 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Hung‐Khoon Tan Hong Kong	14	587	114	77	30	29	35	656
WeiQi Yan Singapore	15	557 0.9×	101 0.9×	70 0.9×	11 0.4×	42 1.4×	60	638
Dongming Zhang China	11	303 0.5×	131 1.1×	77 1.0×	14 0.5×	24 0.8×	65	457
Nianhua Xie China	8	529 0.9×	119 1.0×	135 1.8×	15 0.5×	43 1.5×	10	625
Tiezheng Ge China	11	654 1.1×	187 1.6×	87 1.1×	68 2.3×	71 2.4×	33	774
Guangnan Ye United States	14	788 1.3×	292 2.6×	85 1.1×	13 0.4×	42 1.4×	26	876
Jinfeng Zhuang Singapore	9	199 0.3×	165 1.4×	27 0.4×	7 0.2×	19 0.7×	16	349
Litao Yu Australia	8	262 0.4×	174 1.5×	18 0.2×	7 0.2×	38 1.3×	27	399
Ke Gao China	12	243 0.4×	90 0.8×	41 0.5×	75 2.5×	32 1.1×	44	383
Yuling Liu China	13	225 0.4×	198 1.7×	100 1.3×	13 0.4×	19 0.7×	73	564
Haila Wang China	11	414 0.7×	208 1.8×	194 2.5×	5 0.2×	6 0.2×	45	587

Countries citing papers authored by Hung‐Khoon Tan

Since Specialization

Citations

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

Fields of papers citing papers by Hung‐Khoon Tan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hung‐Khoon Tan. 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 Hung‐Khoon Tan. The network helps show where Hung‐Khoon Tan may publish in the future.

Co-authorship network of co-authors of Hung‐Khoon Tan

This figure shows the co-authorship network connecting the top 25 collaborators of Hung‐Khoon Tan. A scholar is included among the top collaborators of Hung‐Khoon Tan 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 Hung‐Khoon Tan. Hung‐Khoon Tan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Tan, Hung‐Khoon, et al.. (2021). Regularization of Deep Neural Network With Batch Contrastive Loss. IEEE Access. 9. 124409–124418. 9 indexed citations

Ng, Hui‐Fuang, et al.. (2021). Plant Disease Detection Mobile Application Development using Deep Learning. 34–38. 9 indexed citations

Ng, Hui‐Fuang, et al.. (2021). DoubleQExt: Hardware and Memory Efficient CNN Through Two Levels of Quantization. IEEE Access. 9. 169082–169091. 8 indexed citations

Tan, Hung‐Khoon, et al.. (2021). 3D deformable convolution for action classification in videos. 3 indexed citations

Tan, Hung‐Khoon, et al.. (2013). State-of-the-Art Review and Critical Success Factors for Mobile Business Intelligence. Own your potential (DEAKIN). 1–10. 5 indexed citations

Ngo, Chong‐Wah, Shiai Zhu, Wěi Zhāng, et al.. (2011). VIREO @ TRECVID 2011: Instance Search, Semantic Indexing, Multimedia Event Detection and Known-Item Search.. Institutional Knowledge (InK) - Institutional Knowledge at Singapore Management University (Singapore Management University). 1 indexed citations

Hong, Richang, Jinhui Tang, Hung‐Khoon Tan, et al.. (2011). Beyond search. ACM Transactions on Multimedia Computing Communications and Applications. 7(4). 1–18. 74 indexed citations

Ngo, Chong‐Wah, Shiai Zhu, Hung‐Khoon Tan, Wan‐Lei Zhao, & Xiao-Yong Wei. (2010). VIREO at TRECVID 2010: Semantic Indexing, Known-Item Search, and Content-Based Copy Detection. Institutional Knowledge (InK) - Institutional Knowledge at Singapore Management University (Singapore Management University). 6 indexed citations

Tan, Hung‐Khoon, Chong‐Wah Ngo, & Tat‐Seng Chua. (2010). Efficient Mining of Multiple Partial Near-Duplicate Alignments by Temporal Network. IEEE Transactions on Circuits and Systems for Video Technology. 20(11). 1486–1498. 14 indexed citations

10.

Chua, Tat‐Seng, et al.. (2009). MovieBase. National University of Singapore. 41–48. 6 indexed citations

11.

Hong, Richang, Jinhui Tang, Hung‐Khoon Tan, et al.. (2009). Event driven summarization for web videos. National University of Singapore. 43–48. 23 indexed citations

12.

Wu, Xiao, Chong‐Wah Ngo, Alexander G. Hauptmann, & Hung‐Khoon Tan. (2009). Real-Time Near-Duplicate Elimination for Web Video Search With Content and Context. IEEE Transactions on Multimedia. 11(2). 196–207. 97 indexed citations

13.

Ngo, Chong‐Wah, Yu–Gang Jiang, Xiao-Yong Wei, et al.. (2008). Beyond Semantic Search: What You Observe May Not Be What You Think.. Institutional Knowledge (InK) - Institutional Knowledge at Singapore Management University (Singapore Management University). 6 indexed citations

14.

Tan, Hung‐Khoon, Chong‐Wah Ngo, & Xiao Wu. (2008). Modeling video hyperlinks with hypergraph for web video reranking. 659–662. 16 indexed citations

15.

Ngo, Chong‐Wah, Yu–Gang Jiang, Xiao-Yong Wei, et al.. (2007). Experimenting VIREO-374: Bag-of-Visual-Words and Visual-Based Ontology for Semantic Video Indexing and search.. TRECVID. 105(6). 824–32. 15 indexed citations

16.

Jiang, Yu–Gang, Xiao-Yong Wei, Chong‐Wah Ngo, et al.. (2006). Modeling Local Interest Points for Semantic Detection and Video Search at TRECVID 2006.. Institutional Knowledge (InK) - Institutional Knowledge at Singapore Management University (Singapore Management University). 3 indexed citations

17.

Ngo, Chong‐Wah, et al.. (2005). Motion Driven Approaches to Shot Boundary Detection, Low-Level Feature Extraction and BBC Rushes Characterization at TRECVID 2005.. TRECVID. 6 indexed citations

18.

Tan, Hung‐Khoon & Chong‐Wah Ngo. (2005). Common pattern discovery using earth mover's distance and local flow maximization. 1222–1229 Vol. 2. 28 indexed citations

19.

Jiang, Hui, Chong‐Wah Ngo, & Hung‐Khoon Tan. (2005). Gestalt-based feature similarity measure in trademark database. Pattern Recognition. 39(5). 988–1001. 21 indexed citations

20.

Turner, Stephen John, Wentong Cai, & Hung‐Khoon Tan. (2002). Parallel programming with VPE: a case study of an integrated visual programming environment. 319–324.

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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