Xin Wang

10.1k citations
463 papers · 6.6k indexed · 1 hit paper · h-index 44

Impact in

Papers in

Xin Wang

428 papers receiving 6.3k citations

Hit Papers

Few-Shot Object Detection via Feature Reweighting 2019 · 468 citations
4682019202620212023100200300400

Peers

Xin Wang
Comparison fields: 5 of 185
  • Computational Mathematics 318
  • Computer Networks and Communications 2.7k
  • Computer Vision and Pattern Recognition 1.4k
  • Artificial Intelligence 1.7k
  • Signal Processing 519
Replace Zhikui Chen with:
Zhikui Chen China
Chao Zhang China
João Gama Portugal
Qingchen Zhang China
Xiaokang Zhou Japan
Volker Tresp Germany
Qun Li China
Christopher Leckie Australia
Xiaowen Chu Hong Kong
Yi Zhang China
Xin Wang relative to Zhikui Chen China Zhikui Chen's profile →
Citations per field
00.5×3.3×
Zhikui Chen · 1×
Citations per year

Countries citing papers authored by Xin Wang

Since Specialization
Citations

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

Fields of papers citing papers by Xin Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown
#Work
1 20250
2 20253
3 20241
4 20243
5 20240
6 20244
7 20247
8 20240
9 20244
10 20231
11 20232
12 20230
13 20236
14 20203
15 201913
16 201712
17 201721
18 20131
19
MPEG-M: A Digital Media Ecosystem for Interoperable Applications
20131
20
A improved particle swarm optimization algorithm of DOA estimation
20091

About Xin Wang

Xin Wang is a scholar working on Computational Mathematics, Computer Networks and Communications, Computer Vision and Pattern Recognition, Hardware and Architecture and Signal Processing, having authored 463 papers that have together received 6.6k indexed citations. Recurring topics across this work include Caching and Content Delivery (48 papers), Sparse and Compressive Sensing Techniques (42 papers), Network Security and Intrusion Detection (37 papers), Software-Defined Networks and 5G (35 papers), Cloud Computing and Resource Management (32 papers), Network Traffic and Congestion Control (23 papers), Tensor decomposition and applications (22 papers) and IoT and Edge/Fog Computing (22 papers). The work is most often cited by research in Computational Mathematics (318 citations), Computer Networks and Communications (2.7k citations), Computer Vision and Pattern Recognition (1.4k citations), Artificial Intelligence (1.7k citations) and Signal Processing (519 citations). Xin Wang has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Kun Xie, Jigang Wen, Gaogang Xie, Dafang Zhang, Jiannong Cao, Fisher Yu, Trevor Darrell, Jiashi Feng, Bingyi Kang and Zhuang Liu. Their work appears in journals such as IEEE/ACM Transactions on Networking, IEEE Transactions on Mobile Computing, Computer Networks, IEEE Transactions on Services Computing and IEEE Transactions on Dependable and Secure Computing.

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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