Yuan Dong

2.2k citations
100 papers · 833 indexed · h-index 13

Yuan Dong

90 papers receiving 783 citations

Peers

Yuan Dong
Comparison fields: 5 of 96
  • Computer Vision and Pattern Recognition 403
  • Computer Science Applications 76
  • Signal Processing 148
  • Artificial Intelligence 363
  • Media Technology 35
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Citations per field
00.5×4.5×
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Citations per year

Countries citing papers authored by Yuan Dong

Since Specialization
Citations

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

Fields of papers citing papers by Yuan Dong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20250
2 20251
3 20252
4 20251
5 20250
6 20242
7 20240
8 20234
9 202312
10 20236
11
ATRM: Attention-based Task-level Relation Module for GNN-based Few-shot Learning.
20211
12
Multi-branch Siamese Network for High Performance Online Visual Tracking
20191
13 20183
14 201522
15
The France Telecom Orange Labs (Beijing) Video Semantic Indexing Systems - TRECVID 2010 Notebook Paper
20105
16
The France Telecom Orange Labs (Beijing) Video High-level Feature Extraction Systems - TrecVid 2009 Notebook Paper.
20092
17
Support vector machines based text dependent speaker verification using HMM supervectors.
20087
18
Chinese Word Segmentation and Named Entity Recognition Based on Conditional Random Fields
200816
19
Using Non-Local Features to Improve Named Entity Recognition Recall
20075
20
France Telecom R&D Beijing Word Segmenter for Sighan Bakeoff 2006
20064

About Yuan Dong

Yuan Dong is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Artificial Intelligence, having authored 100 papers that have together received 833 indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (19 papers), Video Analysis and Summarization (18 papers), Advanced Image and Video Retrieval Techniques (18 papers), Video Surveillance and Tracking Methods (16 papers), Speech and Audio Processing (15 papers), Music and Audio Processing (15 papers), Natural Language Processing Techniques (15 papers) and Domain Adaptation and Few-Shot Learning (14 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (403 citations), Computer Science Applications (76 citations) and Signal Processing (148 citations). Yuan Dong has collaborated with scholars based in China, France and United Kingdom. Frequent co-authors include Hongliang Bai, Shiguo Lian, Haila Wang, Zhiqun He, Junfei Zhuang, Guoliang Li, Yingruo Fan, Qi Li, Kui Ren and Qian Wang. Their work appears in journals such as IEEE Access, Computer Standards & Interfaces, IEEE Transactions on Information Forensics and Security, Neurocomputing and Tsinghua Science & Technology.

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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