Xingyu Liao

4.7k citations
44 papers · 1.5k indexed · 3 hit papers · h-index 14
Topics
Genomics and Phylogenetic Studies (16 papers)RNA and protein synthesis mechanisms (12 papers)Gene expression and cancer classification (8 papers)
Partner nations
ChinaSaudi ArabiaCanada

In The Last Decade

Xingyu Liao

42 papers receiving 1.4k citations

Hit Papers

Bag of Tricks and a Strong Baseline for Deep Person Re-Id...2019202620212023201920232024250500750

Peers

Xingyu Liao
Comparison fields: 5 of 119
  • Computer Vision and Pattern Recognition 928
  • Molecular Biology 320
  • Biomedical Engineering 286
  • Artificial Intelligence 176
  • Plant Science 75
Replace Hantao Yao with:
Hantao Yao China
Haigen Hu China
Gaoang Wang China
Adel Hafiane France
Xiaohong Jia China
Tsubasa Hirakawa Japan
Erik Rodner Germany
Romuere Silva Brazil
Abu Sufian India
Dan Popescu Romania
Xingyu Liao relative to Hantao Yao China Hantao Yao's profile →
Citations per field
00.5×3.3×
Hantao Yao · 1×
Citations per year

Countries citing papers authored by Xingyu Liao

Since Specialization
Citations

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

Fields of papers citing papers by Xingyu Liao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xingyu Liao

This figure shows the co-authorship network connecting the top 25 collaborators of Xingyu Liao. A scholar is included among the top collaborators of Xingyu Liao 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 Xingyu Liao. Xingyu Liao 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 0
2 1
3
Pre-trained multimodal large language model enhances dermatological diagnosis using SkinGPT-4breakdown →
57
4 2
5 4
6 5
7 0
8 1
9 29
10 3
11 62
12 9
13 2
14 15
15 5
16 18
17
FastReID: A Pytorch Toolbox for Real-world Person Re-identification
13
18 9
19
Bag of Tricks and a Strong Baseline for Deep Person Re-Identificationbreakdown →
864
20 1

About Xingyu Liao

Xingyu Liao is a scholar working on Health Informatics, Applied Microbiology and Biotechnology and Computer Vision and Pattern Recognition, having authored 44 papers that have together received 1.5k indexed citations. Recurring topics across this work include Genomics and Phylogenetic Studies (16 papers), RNA and protein synthesis mechanisms (12 papers) and Gene expression and cancer classification (8 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (928 citations), Health Informatics (24 citations) and Biomedical Engineering (286 citations). Xingyu Liao has collaborated with scholars based in China, Saudi Arabia and Canada. Frequent co-authors include Shenqi Lai, Hao Luo, Wei Jiang, Xin Gao, Jianxin Wang, Juexiao Zhou, Bin Zhang, Fang‐Xiang Wu, Haoyang Li and Min Li. Their work appears in journals such as Nucleic Acids Research, Nature Communications and Bioinformatics.

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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