Howard Cheng

977 citations
26 papers · 580 · h-index 9

Impact in

Papers in

Howard Cheng

24 papers receiving 504 citations

Peers

Howard Cheng
Comparison fields: 5 of 38
  • Computer Vision and Pattern Recognition 481
  • Signal Processing 91
  • Computational Theory and Mathematics 100
  • Artificial Intelligence 186
  • Mathematical Physics 43
Replace Chuan-Kun Wu with:
Chuan-Kun Wu China
Thomas Bühler Germany
Ruisong Ye China
Henk C. A. van Tilborg Netherlands
Juliano B. Lima Brazil
Luis Rademacher United States
Mario Di Raimondo Italy
Iraj Kalantari United States
Antoine Joux France
Peter Kornerup Denmark
Howard Cheng relative to Chuan-Kun Wu China Chuan-Kun Wu's profile →
Citations per field
00.5×8.6×
Chuan-Kun Wu · 1×
Citations per year

Countries citing papers authored by Howard Cheng

Since Specialization
Citations

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

Fields of papers citing papers by Howard Cheng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 17 scholars most cited alongside Howard Cheng, 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 Howard Cheng Line = papers co-authored together Howard Cheng links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 26 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2000371
2 199749
3 200537
4 201520
5 200914
6 201812
7
A Unified Framework for Image Set Compression.
200611
8 20069
9 20028
10 20156
11 20156
12 19976
13 20075
14
A Study of Prediction Measures for Lossy Image Set Compression.
20084
15
Wavelet-based Prediction Measures for Lossy Image Set Compression.
20104
16 20074
17
What makes a Tree a Straight Skeleton
20122
18
Hierarchical Minimum Spanning Trees for Lossy Image Set Compression.
20082
19 20062
20 20052

About Howard Cheng

Howard Cheng is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Computational Theory and Mathematics, Signal Processing and Information Systems, having authored 26 papers that have together received 580 indexed citations. Recurring topics across this work include Advanced Data Compression Techniques (11 papers), Polynomial and algebraic computation (8 papers), Algorithms and Data Compression (8 papers), Image and Signal Denoising Methods (5 papers), Coding theory and cryptography (5 papers), Numerical Methods and Algorithms (5 papers), Speech and Audio Processing (3 papers) and Cryptography and Residue Arithmetic (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (481 citations), Signal Processing (91 citations), Computational Theory and Mathematics (100 citations), Artificial Intelligence (186 citations) and Mathematical Physics (43 citations). Howard Cheng has collaborated with scholars based in Canada, France and Austria. Frequent co-authors include Xiaobo Li, George Labahn, Mohammad Akbari, Bernhard Beckermann, Jie Liang, X. Li, Marc Moreau, Joseph Modayil, Eugene V. Zima and Xiaobo Li. Their work appears in journals such as Pattern Recognition, Pattern Recognition Letters, Multimedia Tools and Applications, IEEE Transactions on Multimedia and IEEE Transactions on Signal Processing.

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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