Danwei Cai

588 citations
24 papers · 298 · h-index 11

Impact in

Papers in

Danwei Cai

23 papers receiving 281 citations

Peers

Danwei Cai
Comparison fields: 5 of 34
  • Signal Processing 265
  • Artificial Intelligence 261
  • Computer Vision and Pattern Recognition 39
  • Physiology 26
  • Experimental and Cognitive Psychology 9
Replace Debadatta Pati with:
Debadatta Pati India
Vadim Shchemelinin Russia
Mahsa Yarmohammadi United States
Sergey Novoselov Russia
Natalia Tomashenko France
Rosa González Hautamäki Finland
Hossein Hadian Iran
Yatharth Saraf United States
Oleg Kudashev Finland
Stephen Shum United States
Danwei Cai relative to Debadatta Pati India Debadatta Pati's profile →
Citations per field
00.5×3.2×
Debadatta Pati · 1×
Citations per year

Countries citing papers authored by Danwei Cai

Since Specialization
Citations

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

Fields of papers citing papers by Danwei Cai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 16 scholars most cited alongside Danwei Cai, 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 Danwei Cai Line = papers co-authored together Danwei Cai links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201748
2 201943
3 202032
4 202123
5 201721
6 201919
7 202214
8 201713
9 201912
10 202212
11 201911
12 20239
13 20248
14 20226
15 20186
16 20185
17 20174
18 20234
19 20212
20 20162

About Danwei Cai

Danwei Cai is a scholar working on Artificial Intelligence, Signal Processing, Physiology, Experimental and Cognitive Psychology and Information Systems, having authored 24 papers that have together received 298 indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (23 papers), Speech and Audio Processing (20 papers), Music and Audio Processing (14 papers), Voice and Speech Disorders (3 papers), Phonetics and Phonology Research (2 papers), Chaos-based Image/Signal Encryption (1 paper), Magnetic confinement fusion research (1 paper) and Quantum chaos and dynamical systems (1 paper). The work is most often cited by research in Signal Processing (265 citations), Artificial Intelligence (261 citations), Computer Vision and Pattern Recognition (39 citations), Physiology (26 citations) and Experimental and Cognitive Psychology (9 citations). Danwei Cai has collaborated with scholars based in China, United States and Malaysia. Frequent co-authors include Ming Li, Weicheng Cai, Xiaoyi Qin, Wenbo Liu, Haiwei Wu, Gang Li, Weiqing Wang, Ming Li, Bok‐Min Goi and Wun‐She Yap. Their work appears in journals such as IEEE/ACM Transactions on Audio Speech and Language Processing, Pattern Recognition and Conference of the International Speech Communication Association.

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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