Ee-Leng Tan

43 papers receiving 914 citations

Peers

Ee-Leng Tan
Comparison fields: 5 of 102
  • Signal Processing 237
  • Computer Vision and Pattern Recognition 277
  • Cognitive Neuroscience 206
  • Neurology 76
  • Artificial Intelligence 271
Replace Emad Fatemizadeh with:
Emad Fatemizadeh Iran
Mohamed Hédi Bedoui Tunisia
Adel S. El‐Fishawy Egypt
Pushpendra Singh India
F.H.Y. Chan Hong Kong
Qisong Wu China
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Ee-Leng Tan relative to Emad Fatemizadeh Iran Emad Fatemizadeh's profile →
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Citations per year

Countries citing papers authored by Ee-Leng Tan

Since Specialization
Citations

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

Fields of papers citing papers by Ee-Leng Tan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ee-Leng Tan. 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 Ee-Leng Tan. The network helps show where Ee-Leng Tan may publish in the future.

Co-authors

The 25 scholars most cited alongside Ee-Leng Tan, 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 Ee-Leng Tan Line = papers co-authored together Ee-Leng Tan links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 43 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016187
2 2022102
3 201395
4 202169
5 201543
6 202040
7 201740
8 201039
9 201537
10 202033
11 201025
12 200925
13 201417
14 201516
15 200615
16 198915
17 202113
18
Spatial sound reproduction using conventional and parametric loudspeakers
201212
19
Individualization of Binaural Synthesis Using Frontal Projection Headphones
201311
20 201311

About Ee-Leng Tan

Ee-Leng Tan is a scholar working on Signal Processing, Computer Vision and Pattern Recognition, Cognitive Neuroscience, Computational Mechanics and Neurology, having authored 43 papers that have together received 942 indexed citations. Recurring topics across this work include Speech and Audio Processing (18 papers), Advanced Adaptive Filtering Techniques (9 papers), Hearing Loss and Rehabilitation (9 papers), Parkinson's Disease Mechanisms and Treatments (6 papers), Music and Audio Processing (5 papers), Voice and Speech Disorders (5 papers), Blind Source Separation Techniques (4 papers) and Acoustic Wave Phenomena Research (4 papers). The work is most often cited by research in Signal Processing (237 citations), Computer Vision and Pattern Recognition (277 citations), Cognitive Neuroscience (206 citations), Neurology (76 citations) and Artificial Intelligence (271 citations). Ee-Leng Tan has collaborated with scholars based in Singapore, China and United States. Frequent co-authors include Baiying Lei, Woon‐Seng Gan, Tianfu Wang, Ing Yann Soon, Dong Ni, Siping Chen, Xudong Jiang, Youyi Song, Jie‐Zhi Cheng and Jianjun He. Their work appears in journals such as IEEE/ACM Transactions on Audio Speech and Language Processing, IEEE Signal Processing Magazine, Journal of the Audio Engineering Society, Expert Systems with Applications and Medical Image Analysis.

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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