Yifeng Dai

25 papers receiving 375 citations

Hit Papers

Intern VL: Scaling up Vision Foundation Models and Aligni...20242026202520242024255075100

Peers

Yifeng Dai
Comparison fields: 5 of 94
  • Computer Vision and Pattern Recognition 121
  • Food Science 78
  • Organic Chemistry 59
  • Molecular Biology 53
  • Artificial Intelligence 53
Replace Xiaojuan Zhang with:
Xiaojuan Zhang China
Chaoxin Zheng Ireland
Alexandre Gonçalves Silva Brazil
C. Boucon Netherlands
Yiying Zhao China
Mondher Frikha Tunisia
Sylvie Roussel France
Mahdi Saadatmand‐Tarzjan Iran
A. Karthik India
Yifeng Dai relative to Xiaojuan Zhang China Xiaojuan Zhang's profile →
Citations per field
00.5×8.4×
Xiaojuan Zhang · 1×
Citations per year

Countries citing papers authored by Yifeng Dai

Since Specialization
Citations

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

Fields of papers citing papers by Yifeng Dai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yifeng Dai

This figure shows the co-authorship network connecting the top 25 collaborators of Yifeng Dai. A scholar is included among the top collaborators of Yifeng Dai 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 Yifeng Dai. Yifeng Dai is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 1
2 0
3 1
4 1
5
Intern VL: Scaling up Vision Foundation Models and Aligning for Generic Visual-Linguistic Tasksbreakdown →
105
6 17
7 0
8 0
9
Efficient Deformable ConvNets: Rethinking Dynamic and Sparse Operator for Vision Applicationsbreakdown →
66
10 20
11 8
12 1
13 14
14 17
15 3
16 3
17 4
18 6
19 13
20 21

About Yifeng Dai

Yifeng Dai is a scholar working on Food Science, Computer Vision and Pattern Recognition and Biotechnology, having authored 28 papers that have together received 385 indexed citations. Recurring topics across this work include Fermentation and Sensory Analysis (7 papers), Analytical Chemistry and Chromatography (3 papers) and Asymmetric Synthesis and Catalysis (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (121 citations), Food Science (78 citations) and Computer Graphics and Computer-Aided Design (8 citations). Yifeng Dai has collaborated with scholars based in China, Hong Kong and Singapore. Frequent co-authors include Wenhai Wang, Tong Lü, Xizhou Zhu, Shuyi Qiu, Yu Qiao, Shaoxiang Yang, Hongyu Tian, Yongguo Liu, Sen Xing and Zhe Chen. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Journal of Agricultural and Food Chemistry and International Journal of Food Microbiology.

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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