Xiangtai Li

3.9k citations
58 papers · 1.6k indexed · 6 hit papers · h-index 18
Topics
Advanced Neural Network Applications (21 papers)Advanced Image and Video Retrieval Techniques (20 papers)Multimodal Machine Learning Applications (19 papers)

In The Last Decade

Xiangtai Li

54 papers receiving 1.5k citations

Hit Papers

Involution: Inverting the Inherence of Convolution for Vi...20212026202220242021202320242024202450100150200250

Peers

Xiangtai Li
Comparison fields: 5 of 113
  • Computer Vision and Pattern Recognition 936
  • Artificial Intelligence 347
  • Media Technology 263
  • Electrical and Electronic Engineering 161
  • Aerospace Engineering 117
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Xiangtai Li relative to Jian Cheng China Jian Cheng's profile →
Citations per field
00.5×4.7×
Jian Cheng · 1×
Citations per year

Countries citing papers authored by Xiangtai Li

Since Specialization
Citations

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

Fields of papers citing papers by Xiangtai Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xiangtai Li

This figure shows the co-authorship network connecting the top 25 collaborators of Xiangtai Li. A scholar is included among the top collaborators of Xiangtai Li 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 Xiangtai Li. Xiangtai Li 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 8
2 1
3 1
4 3
5 2
6
Towards Open Vocabulary Learning: A Surveybreakdown →
64
7 7
8
Change Detection Methods for Remote Sensing in the Last Decade: A Comprehensive Reviewbreakdown →
78
9 6
10 5
11 3
12 11
13 16
14 30
15 103
16 47
17
Involution: Inverting the Inherence of Convolution for Visual Recognitionbreakdown →
264
18 87
19
Global Aggregation then Local Distribution in Fully Convolutional Networks.
8
20
Dual Graph Convolutional Network for Semantic Segmentation.
23

About Xiangtai Li

Xiangtai Li is a scholar working on Computer Vision and Pattern Recognition, Geology and Artificial Intelligence, having authored 58 papers that have together received 1.6k indexed citations. Recurring topics across this work include Advanced Neural Network Applications (21 papers), Advanced Image and Video Retrieval Techniques (20 papers) and Multimodal Machine Learning Applications (19 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (936 citations), Media Technology (263 citations) and Artificial Intelligence (347 citations). Xiangtai Li has collaborated with scholars based in China, Singapore and United Kingdom. Frequent co-authors include Yunhai Tong, Guangliang Cheng, Duo Li, Jie Hu, Lei Zhu, Qi She, Changhu Wang, Qifeng Chen, Kuiyuan Yang and Tong Zhang. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Journal of The Electrochemical Society and Applied Catalysis B: Environmental.

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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