Tianyu Fu

556 citations
16 papers · 239 indexed · h-index 6
Topics
Robot Manipulation and Learning (7 papers)Industrial Vision Systems and Defect Detection (6 papers)Manufacturing Process and Optimization (4 papers)
Journals
SHILAP Revista de lepidopterologíaAdvanced Functional MaterialsSensors
Partner nations
ChinaUnited StatesFrance

In The Last Decade

Tianyu Fu

13 papers receiving 234 citations

Peers

Tianyu Fu
Comparison fields: 5 of 38
  • Computer Vision and Pattern Recognition 178
  • Signal Processing 136
  • Artificial Intelligence 29
  • Industrial and Manufacturing Engineering 28
  • Control and Systems Engineering 23
Replace Ankan Bansal with:
Ankan Bansal United States
Mandi Luo China
Rizhao Cai Singapore
Jingxiao Zheng United States
Yanxiang Chen China
Yosef A. Solewicz Israel
Guanzhong Tian China
Yi-Ping Hung Taiwan
Tie Liu China
Wenchao Zhang China
Tianyu Fu relative to Ankan Bansal United States Ankan Bansal's profile →
Citations per field
00.5×4.7×
Ankan Bansal · 1×
Citations per year

Countries citing papers authored by Tianyu Fu

Since Specialization
Citations

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

Fields of papers citing papers by Tianyu Fu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tianyu Fu

This figure shows the co-authorship network connecting the top 25 collaborators of Tianyu Fu. A scholar is included among the top collaborators of Tianyu Fu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Tianyu Fu. Tianyu Fu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

16 of 16 papers shown
#WorkIndexed citations
1 0
2 0
3 1
4 1
5 2
6 0
7 1
8 1
9 2
10 6
11 6
12 7
13
Learning meta model for zero- and few-shot face anti-spoofing
75
14 20
15 113
16 4

About Tianyu Fu

Tianyu Fu is a scholar working on Industrial and Manufacturing Engineering, Control and Systems Engineering and Instrumentation, having authored 16 papers that have together received 239 indexed citations. Recurring topics across this work include Robot Manipulation and Learning (7 papers), Industrial Vision Systems and Defect Detection (6 papers) and Manufacturing Process and Optimization (4 papers). The work is most often cited by research in Signal Processing (136 citations), Computer Vision and Pattern Recognition (178 citations) and Industrial and Manufacturing Engineering (28 citations). Tianyu Fu has collaborated with scholars based in China, United States and France. Frequent co-authors include Shuo Wang, Hailin Shi, Xiaobo Wang, Tao Mei, Shifeng Zhang, Xiangyu Zhu, Zhen Lei, Yunxiao Qin, Chenxu Zhao and Jingping Shi. Their work appears in journals such as SHILAP Revista de lepidopterología, Advanced Functional Materials and Sensors.

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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