Yao Ding

788 citations
15 papers · 495 · 1 hit paper · h-index 7

Impact in

Papers in

Yao Ding

13 papers receiving 487 citations

Yao Ding's Hit Papers

Effective Fusion Factor in FPN for Tiny Object Detection 2021 · 220 citations
2200+1+3Years since publication50100150200

Peers

Yao Ding
Comparison fields: 5 of 64
  • Computer Vision and Pattern Recognition 341
  • Media Technology 53
  • Artificial Intelligence 140
  • Pharmaceutical Science 24
  • Industrial and Manufacturing Engineering 35
Replace Xuan Luo with:
Xuan Luo China
Ruiping Liu China
Yinan Zhao China
Ke Xie China
Qin Huang China
Zhuofan Zong China
James Gabriel United States
Dan Yao China
Sumin Lee South Korea
Shengkai Wu China
Yao Ding relative to Xuan Luo China Xuan Luo's profile →
Citations per field
00.5×
Xuan Luo · 1×
Citations per year

Countries citing papers authored by Yao Ding

Since Specialization
Citations

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

Fields of papers citing papers by Yao Ding

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

15 of 15 papers shown
#Work
1
Effective Fusion Factor in FPN for Tiny Object Detection
Hit paper breakdown →
2021220
2 2019182
3 201630
4 202114
5 201913
6 20187
7 20196
8 20256
9 20225
10 20225
11 20204
12 20171
13 20251
14 20201
15 20260

About Yao Ding

Yao Ding is a scholar working on Computer Vision and Pattern Recognition, Organic Chemistry, Artificial Intelligence, Experimental and Cognitive Psychology and Electronic, Optical and Magnetic Materials, having authored 15 papers that have together received 495 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (3 papers), Face and Expression Recognition (2 papers), Catalytic C–H Functionalization Methods (2 papers), Face recognition and analysis (2 papers), Domain Adaptation and Few-Shot Learning (2 papers), Synthesis and Catalytic Reactions (2 papers), Industrial Vision Systems and Defect Detection (2 papers) and Emotion and Mood Recognition (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (341 citations), Media Technology (53 citations), Artificial Intelligence (140 citations), Pharmaceutical Science (24 citations) and Industrial and Manufacturing Engineering (35 citations). Yao Ding has collaborated with scholars based in China, Singapore and United States. Frequent co-authors include Zhenjun Han, Qixiang Ye, Yanzhao Zhou, Yi Zhu, Jianbin Jiao, Yuqi Gong, Xuehui Yu, Jian Zhao, Yang Xi and Rong Zhang. Their work appears in journals such as Chemical Communications, Organic & Biomolecular Chemistry, Advanced Science, Construction and Building Materials and IEEE Transactions on Circuits and Systems for Video 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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