Lei Ji

876 total citations
27 papers, 272 citations indexed

About

Lei Ji is a scholar working on Computer Vision and Pattern Recognition, Electrical and Electronic Engineering and Media Technology. According to data from OpenAlex, Lei Ji has authored 27 papers receiving a total of 272 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Computer Vision and Pattern Recognition, 10 papers in Electrical and Electronic Engineering and 8 papers in Media Technology. Recurrent topics in Lei Ji's work include Multimodal Machine Learning Applications (7 papers), Human Pose and Action Recognition (4 papers) and Image and Video Quality Assessment (4 papers). Lei Ji is often cited by papers focused on Multimodal Machine Learning Applications (7 papers), Human Pose and Action Recognition (4 papers) and Image and Video Quality Assessment (4 papers). Lei Ji collaborates with scholars based in China, United States and Singapore. Lei Ji's co-authors include Zhiyong Feng, Qixun Zhang, Wei Li, Zhiyong Chen, Zhu Han, Nan Duan, Xiang Huang, Huaishao Luo, Ming Zhou and Xilin Chen and has published in prestigious journals such as IEEE Communications Magazine, IEEE Transactions on Wireless Communications and IEEE Transactions on Vehicular Technology.

In The Last Decade

Lei Ji

23 papers receiving 266 citations

Peers

Lei Ji
Comparison fields: 5 of 40
  • Aerospace Engineering 152
  • Computer Networks and Communications 105
  • Computer Vision and Pattern Recognition 101
  • Electrical and Electronic Engineering 98
  • Artificial Intelligence 41
Replace Zeyang Meng with:
Zeyang Meng China
Kailing Yao China
Jiansong Miao China
Guangyuan Zheng China
Weiyu Wu China
Fusheng Zhu China
Do-Yup Kim South Korea
Chethan Kumar Anjinappa United States
Mohamed I. AlHajri United Arab Emirates
Ajmery Sultana Canada
Zeyang Meng China View profile →
Citations per field, relative to Lei Ji
Lei Ji · 1×
Citations per year, relative to Lei Ji
Lei Ji · 1×

Countries citing papers authored by Lei Ji

Since Specialization
Citations

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

Fields of papers citing papers by Lei Ji

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lei Ji

This figure shows the co-authorship network connecting the top 25 collaborators of Lei Ji. A scholar is included among the top collaborators of Lei Ji 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 Lei Ji. Lei Ji 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
# Work Indexed citations
1 3
2 0
3 0
4 1
5 6
6 5
7 6
8 8
9
Learning from Inside: Self-driven Siamese Sampling and Reasoning for Video Question Answering
15
10 5
11 15
12 83
13 6
14 1
15 3
16 2
17 2
18
Comparison of Non-Linear Optimum and Linear Iteration Algorithms Applied in the Microwave Tomograph
1
19 1
20
An Optimal Model of Location and Configuration for Emergency Resource Based on Varied Periodic Demands
2

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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