Jin-Jang Leou

1.1k citations
66 papers · 765 indexed · h-index 16

Jin-Jang Leou

59 papers receiving 713 citations

Peers

Jin-Jang Leou
Comparison fields: 5 of 59
  • Computer Vision and Pattern Recognition 687
  • Signal Processing 300
  • Media Technology 112
  • Computer Graphics and Computer-Aided Design 15
  • Sensory Systems 13
Replace Seungjoon Yang with:
Seungjoon Yang South Korea
Diego A. Socolinsky United States
T.E. Boult United States
Zhengxue Cheng Japan
Maria Paula Queluz Portugal
Jo Yew Tham Singapore
Gaurav Aggarwal United States
Long-Wen Chang Taiwan
Jin-Jang Leou relative to Seungjoon Yang South Korea Seungjoon Yang's profile →
Citations per field
00.5×6.5×
Seungjoon Yang · 1×
Citations per year

Countries citing papers authored by Jin-Jang Leou

Since Specialization
Citations

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

Fields of papers citing papers by Jin-Jang Leou

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jin-Jang Leou. 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 Jin-Jang Leou. The network helps show where Jin-Jang Leou may publish in the future.

Co-authorship network

The 9 scholars most cited alongside Jin-Jang Leou, 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 Jin-Jang Leou Line = papers co-authored together Jin-Jang Leou links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20212
2 20144
3
An enhanced seam carving approach for video retargeting
20120
4 20119
5
Visual Attention Region Detection Using Texture and Object Features
20102
6 20103
7
Human Behavior Analysis Using Multiple 2D Features and Multicategory Support Vector Machine.
200917
8 200922
9 20093
10 20092
11 20060
12 200623
13 20061
14 20060
15 20053
16
Detection and Concealment of Transmissions Errors in MPEG-4 Images.
20041
17
A New Approach to Video Format Conversion Using Bidirectional Motion Estimation and Hybrid Error Concealment
20015
18 199511
19
New Fuzzy Hierarchical Clustering Algorithms.
19935
20 19925

About Jin-Jang Leou

Jin-Jang Leou is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Media Technology, having authored 66 papers that have together received 765 indexed citations. Recurring topics across this work include Advanced Vision and Imaging (29 papers), Video Coding and Compression Technologies (27 papers), Advanced Data Compression Techniques (23 papers), Advanced Image Processing Techniques (14 papers), Image and Video Quality Assessment (13 papers), Image Enhancement Techniques (12 papers), Advanced Image and Video Retrieval Techniques (11 papers) and Image and Signal Denoising Methods (8 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (687 citations), Signal Processing (300 citations) and Media Technology (112 citations). Jin-Jang Leou has collaborated with scholars based in Taiwan. Frequent co-authors include Li‐Wei Kang, Hsuan‐Ying Chen, Wen‐Hsiang Tsai, Chi-Yu Lee, Li-Wei Kang, Yi-Jhen Wu, Minghui Cheng, Yi-Lin Tsai and Yu‐Ping Chiu. Their work appears in journals such as IEEE Transactions on Communications, Pattern Recognition and IEEE Transactions on Circuits and Systems for Video Technology.

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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