Hua-Wen Chang

509 citations
20 papers · 397 indexed · h-index 9
Topics
Advanced Image Fusion Techniques (13 papers)Image and Video Quality Assessment (12 papers)Advanced Vision and Imaging (6 papers)
Partner nations
ChinaTaiwan

In The Last Decade

Hua-Wen Chang

19 papers receiving 384 citations

Peers

Hua-Wen Chang
Comparison fields: 5 of 51
  • Computer Vision and Pattern Recognition 365
  • Media Technology 194
  • Signal Processing 61
  • Atomic and Molecular Physics, and Optics 50
  • Electrical and Electronic Engineering 22
Replace Domonkos Varga with:
Domonkos Varga Hungary
Pradip Paudyal Italy
Yifan Zuo China
Zhongfu Ye China
Joe Yuchieh Lin United States
S. Yao Singapore
Phong V. Vu United States
Sergio Goma United States
Balu Adsumilli United States
Jingtao Xu China
Hua-Wen Chang relative to Domonkos Varga Hungary Domonkos Varga's profile →
Citations per field
00.5×8.4×
Domonkos Varga · 1×
Citations per year

Countries citing papers authored by Hua-Wen Chang

Since Specialization
Citations

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

Fields of papers citing papers by Hua-Wen Chang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hua-Wen Chang. 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 Hua-Wen Chang. The network helps show where Hua-Wen Chang may publish in the future.

Co-authorship network of co-authors of Hua-Wen Chang

This figure shows the co-authorship network connecting the top 25 collaborators of Hua-Wen Chang. A scholar is included among the top collaborators of Hua-Wen Chang 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 Hua-Wen Chang. Hua-Wen Chang 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
1 4
2 7
3 1
4 1
5 1
6 3
7 14
8 0
9 29
10 8
11 55
12 2
13 14
14 53
15 122
16 56
17
Sparse feature fidelity for image quality assessment
2
18 13
19 4
20 8

About Hua-Wen Chang

Hua-Wen Chang is a scholar working on Media Technology, Computer Vision and Pattern Recognition and Signal Processing, having authored 20 papers that have together received 397 indexed citations. Recurring topics across this work include Advanced Image Fusion Techniques (13 papers), Image and Video Quality Assessment (12 papers) and Advanced Vision and Imaging (6 papers). The work is most often cited by research in Media Technology (194 citations), Computer Vision and Pattern Recognition (365 citations) and Signal Processing (61 citations). Hua-Wen Chang has collaborated with scholars based in China and Taiwan. Frequent co-authors include Yong Gan, Minghui Wang, Qiuwen Zhang, Qinggang Wu, Shuo Yang, Jie Xu, Bin Lin, Kai Chen, Weiwei Zhang and Pei‐Jun Lee. Their work appears in journals such as IEEE Transactions on Image Processing, Neurocomputing and IEEE Signal Processing Letters.

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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