Jinyu Yang

2.2k citations
43 papers · 1.1k · 1 hit paper · h-index 18

Impact in

Papers in

Jinyu Yang

39 papers receiving 1.1k citations

Jinyu Yang's Hit Papers

Vision-Language Pre-Training with Triple Contrastive Learning 2022 · 170 citations
1700+1+2Years since publication50100150

Peers

Jinyu Yang
Comparison fields: 5 of 138
  • Computer Vision and Pattern Recognition 271
  • Artificial Intelligence 313
  • Clinical Biochemistry 63
  • Health Informatics 10
  • Molecular Biology 487
Replace Chenxin Li with:
Chenxin Li China
Xinyue Liu China
Lonnie R. Welch United States
Yijia Liu China
Jeesoo Kim South Korea
Xiaoli Wang China
Giosuè Lo Bosco Italy
Xiaohui Cheng China
Alfonso Rodríguez‐Patón Spain
S. Karthikeyan United States
Jinyu Yang relative to Chenxin Li China Chenxin Li's profile →
Citations per field
00.5×7.9×
Chenxin Li · 1×
Citations per year

Countries citing papers authored by Jinyu Yang

Since Specialization
Citations

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

Fields of papers citing papers by Jinyu Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 43 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017244
2
Vision-Language Pre-Training with Triple Contrastive Learning
Hit paper breakdown →
2022170
3 202387
4 201947
5 202144
6 201943
7 201743
8 202142
9 201642
10 201942
11 201738
12 202237
13 201729
14 202125
15 202123
16 201822
17 202021
18 201720
19 202215
20 202215

About Jinyu Yang

Jinyu Yang is a scholar working on Molecular Biology, Artificial Intelligence, Computer Vision and Pattern Recognition, Plant Science and Food Science, having authored 43 papers that have together received 1.1k indexed citations. Recurring topics across this work include Genomics and Phylogenetic Studies (6 papers), Domain Adaptation and Few-Shot Learning (5 papers), Multimodal Machine Learning Applications (5 papers), RNA and protein synthesis mechanisms (5 papers), Genomics and Chromatin Dynamics (4 papers), Polysaccharides Composition and Applications (3 papers), Polysaccharides and Plant Cell Walls (3 papers) and Advanced Image and Video Retrieval Techniques (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (271 citations), Artificial Intelligence (313 citations), Clinical Biochemistry (63 citations), Health Informatics (10 citations) and Molecular Biology (487 citations). Jinyu Yang has collaborated with scholars based in China, United States and Germany. Frequent co-authors include Junzhou Huang, Qin Ma, Jiali Duan, Son N. Tran, Li‐Qun Chen, Yi Xu, Belinda Zeng, Trishul Chilimbi, Song Gao and Adam McDermaid. Their work appears in journals such as Bioinformatics, Briefings in Bioinformatics, Journal of Pineal Research, Scientific Reports and Agronomy.

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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