Jiajun Liang

2.6k citations
10 papers · 362 indexed · h-index 8
Topics
Online Learning and Analytics (3 papers)Software System Performance and Reliability (3 papers)Multimodal Machine Learning Applications (2 papers)
Journals
Pattern RecognitionMultimedia Tools and Applications2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

In The Last Decade

Jiajun Liang

8 papers receiving 358 citations

Peers

Jiajun Liang
Comparison fields: 5 of 59
  • Computer Vision and Pattern Recognition 189
  • Computer Science Applications 125
  • Artificial Intelligence 109
  • Media Technology 56
  • Computer Networks and Communications 33
Replace Nithin Raj with:
Nithin Raj India
Paul Swoboda Germany
Manisha Verma United States
Valerio Luconi Italy
Cise Midoglu Norway
Guangzhi Zhang China
Dumitru Dan Burdescu Romania
Feifei Kou China
Zainab Abu Bakar Malaysia
Jiajun Liang relative to Nithin Raj India Nithin Raj's profile →
Citations per field
00.5×10×20×27.5×
Nithin Raj · 1×
Citations per year

Countries citing papers authored by Jiajun Liang

Since Specialization
Citations

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

Fields of papers citing papers by Jiajun Liang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jiajun Liang

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

All Works

10 of 10 papers shown
#WorkIndexed citations
1 0
2 0
3 27
4 26
5 11
6 11
7 148
8 74
9 7
10 58

About Jiajun Liang

Jiajun Liang is a scholar working on Computer Science Applications, Computer Vision and Pattern Recognition and Computer Networks and Communications, having authored 10 papers that have together received 362 indexed citations. Recurring topics across this work include Online Learning and Analytics (3 papers), Software System Performance and Reliability (3 papers) and Multimodal Machine Learning Applications (2 papers). The work is most often cited by research in Computer Science Applications (125 citations), Computer Vision and Pattern Recognition (189 citations) and Media Technology (56 citations). Jiajun Liang has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Zheng Li, Cong Yao, Xiang Bai, Pengyuan Lyu, Jian Zhang, Minghui Liao, Zhaoyi Wan, Jian Yang, Yongji Wu and Yi Zhou. Their work appears in journals such as Pattern Recognition, Multimedia Tools and Applications and 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

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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