Ja-Hwung Su

986 citations
57 papers · 630 indexed · h-index 11
Topics
Image Retrieval and Classification Techniques (20 papers)Advanced Image and Video Retrieval Techniques (17 papers)Video Analysis and Summarization (16 papers)
Partner nations
TaiwanUnited StatesChina

In The Last Decade

Ja-Hwung Su

55 papers receiving 589 citations

Peers

Ja-Hwung Su
Comparison fields: 5 of 67
  • Computer Vision and Pattern Recognition 386
  • Information Systems 203
  • Signal Processing 161
  • Artificial Intelligence 154
  • Computational Theory and Mathematics 73
Replace Nikolaos Pappas with:
Nikolaos Pappas Switzerland
Raffaele Pizzolante Italy
Giorgio Orsi Italy
Fanghua Ye China
Nur Azman Abu Malaysia
Tengchao Lv China
Klaus U. Schulz Germany
Rajshekhar Sunderraman United States
Marcos Aurélio Domingues Brazil
Jiaxing Zhang China
Ja-Hwung Su relative to Nikolaos Pappas Switzerland Nikolaos Pappas's profile →
Citations per field
00.5×6.6×
Nikolaos Pappas · 1×
Citations per year

Countries citing papers authored by Ja-Hwung Su

Since Specialization
Citations

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

Fields of papers citing papers by Ja-Hwung Su

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ja-Hwung Su. 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 Ja-Hwung Su. The network helps show where Ja-Hwung Su may publish in the future.

Co-authorship network of co-authors of Ja-Hwung Su

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

All Works

20 of 20 papers shown
#WorkIndexed citations
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3 1
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5 5
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8 2
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11 5
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13 10
14 5
15 26
16 1
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19 27
20 11

About Ja-Hwung Su

Ja-Hwung Su is a scholar working on Signal Processing, Computer Vision and Pattern Recognition and Information Systems, having authored 57 papers that have together received 630 indexed citations. Recurring topics across this work include Image Retrieval and Classification Techniques (20 papers), Advanced Image and Video Retrieval Techniques (17 papers) and Video Analysis and Summarization (16 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (386 citations), Signal Processing (161 citations) and Information Systems (203 citations). Ja-Hwung Su has collaborated with scholars based in Taiwan, United States and China. Frequent co-authors include Vincent S. Tseng, Philip S. Yu, Vincent S. Tseng, Bowen Wang, Tzung‐Pei Hong, Yuting Huang, Wen-Yang Lin, Jerry Chun‐Wei Lin, Philippe Fournier‐Viger and Ching‐Yung Lin. Their work appears in journals such as Expert Systems with Applications, IEEE Access and Information Sciences.

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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