Mei‐Ling Shyu

6.8k citations
232 papers · 4.7k indexed · 1 hit paper · h-index 33
Topics
Advanced Image and Video Retrieval Techniques (77 papers)Video Analysis and Summarization (71 papers)Image Retrieval and Classification Techniques (57 papers)
Partner nations
United StatesChinaTaiwan

In The Last Decade

Mei‐Ling Shyu

223 papers receiving 4.4k citations

Hit Papers

A Survey on Deep Learning20182026202020232018250500750

Peers

Mei‐Ling Shyu
Comparison fields: 5 of 185
  • Artificial Intelligence 2.1k
  • Computer Vision and Pattern Recognition 1.9k
  • Computer Networks and Communications 721
  • Signal Processing 687
  • Information Systems 594
Replace Markus Hagenbuchner with:
Markus Hagenbuchner Australia
S. S. Iyengar United States
Joshua Zhexue Huang China
Hieu Pham United States
Rui Zhang China
Abbes Amira United Kingdom
Bo Liu China
Fu-Lai Chung Hong Kong
Guodong Long Australia
Cheng Yang China
Mei‐Ling Shyu relative to Markus Hagenbuchner Australia Markus Hagenbuchner's profile →
Citations per field
00.5×10.2×
Markus Hagenbuchner · 1×
Citations per year

Countries citing papers authored by Mei‐Ling Shyu

Since Specialization
Citations

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

Fields of papers citing papers by Mei‐Ling Shyu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mei‐Ling Shyu. 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 Mei‐Ling Shyu. The network helps show where Mei‐Ling Shyu may publish in the future.

Co-authorship network of co-authors of Mei‐Ling Shyu

This figure shows the co-authorship network connecting the top 25 collaborators of Mei‐Ling Shyu. A scholar is included among the top collaborators of Mei‐Ling Shyu 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 Mei‐Ling Shyu. Mei‐Ling Shyu 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 0
3 14
4 3
5 10
6
Deep reinforcement learning for optimized visual field analysis
2
7 6
8 145
9 63
10
A Survey on Deep Learningbreakdown →
915
11 39
12 7
13 1
14 2
15 11
16 10
17
User concept pattern discovery using relevance feedback and multiple instance learning for content-based image retrieval
29
18
Multimedia data mining for traffic video sequences
25
19 9
20
A presentation semantic model for asynchronous distance learning paradigm
0

About Mei‐Ling Shyu

Mei‐Ling Shyu is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Artificial Intelligence, having authored 232 papers that have together received 4.7k indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (77 papers), Video Analysis and Summarization (71 papers) and Image Retrieval and Classification Techniques (57 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.9k citations), Artificial Intelligence (2.1k citations) and Signal Processing (687 citations). Mei‐Ling Shyu has collaborated with scholars based in United States, China and Taiwan. Frequent co-authors include Shu‐Ching Chen, Yudong Tao, Samira Pouyanfar, Yilin Yan, Haiman Tian, S. S. Iyengar, Saad Sadiq, Min Chen, LiWu Chang and Kanoksri Sarinnapakorn. Their work appears in journals such as Journal of Cleaner Production, Scientific Reports and IEEE Transactions on Geoscience and Remote Sensing.

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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