Hsin‐Te Wu

641 citations
55 papers · 458 · h-index 12

Impact in

Papers in

Hsin‐Te Wu

49 papers receiving 436 citations

Peers

Hsin‐Te Wu
Comparison fields: 5 of 83
  • Signal Processing 71
  • Information Systems 147
  • Computer Networks and Communications 141
  • Automotive Engineering 34
  • Computational Mechanics 53
Replace Alireza Ghasempour with:
Alireza Ghasempour United States
Petr Mlýnek Czechia
Rozeha A. Rashid Malaysia
Nan Pan China
M. Arif Khan Australia
Yan Feng China
Justin Patton United States
Eugen Brenner Austria
Xingfu Wang China
Hsin‐Te Wu relative to Alireza Ghasempour United States Alireza Ghasempour's profile →
Citations per field
00.5×4.8×
Alireza Ghasempour · 1×
Citations per year

Countries citing papers authored by Hsin‐Te Wu

Since Specialization
Citations

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

Fields of papers citing papers by Hsin‐Te Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hsin‐Te Wu. 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 Hsin‐Te Wu. The network helps show where Hsin‐Te Wu may publish in the future.

Co-authors

The 25 scholars most cited alongside Hsin‐Te Wu, 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 Hsin‐Te Wu Line = papers co-authored together Hsin‐Te Wu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 55 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201974
2 201847
3 200446
4 202028
5
Optimal Route Planning System for Logistics Vehicles Based on Artificial Intelligence
202020
6 201918
7 201118
8 200317
9 200716
10 202015
11 201813
12 202111
13 202210
14 20199
15 20219
16 20148
17 20248
18 20198
19 20206
20 20216

About Hsin‐Te Wu

Hsin‐Te Wu is a scholar working on Artificial Intelligence, Electrical and Electronic Engineering, Computer Networks and Communications, Information Systems and Computer Vision and Pattern Recognition, having authored 55 papers that have together received 458 indexed citations. Recurring topics across this work include Blockchain Technology Applications and Security (6 papers), Cryptography and Data Security (5 papers), Privacy-Preserving Technologies in Data (5 papers), Vehicular Ad Hoc Networks (VANETs) (4 papers), Water Quality Monitoring Technologies (4 papers), IoT and Edge/Fog Computing (4 papers), Advanced Adaptive Filtering Techniques (3 papers) and IoT-based Smart Home Systems (3 papers). The work is most often cited by research in Signal Processing (71 citations), Information Systems (147 citations), Computer Networks and Communications (141 citations), Automotive Engineering (34 citations) and Computational Mechanics (53 citations). Hsin‐Te Wu has collaborated with scholars based in Taiwan, China and United States. Frequent co-authors include Chun‐Wei Tsai, Mu‐Yen Chen, Fan‐Hsun Tseng, Fu‐Kun Chen, S.M. Kuo, Wen‐Shyong Hsieh, Hsin‐Hung Cho, Changyi Yang, Gautam Srivastava and Wu-Chih Hu. Their work appears in journals such as Journal of Organizational and End User Computing, Enterprise Information Systems, IEEE Consumer Electronics Magazine, Frontiers in Psychology and Human-centric Computing and Information Sciences.

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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