Genlin Ji

5.4k total citations · 2 hit papers
145 papers, 4.0k citations indexed

About

Genlin Ji is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems. According to data from OpenAlex, Genlin Ji has authored 145 papers receiving a total of 4.0k indexed citations (citations by other indexed papers that have themselves been cited), including 62 papers in Artificial Intelligence, 52 papers in Computer Vision and Pattern Recognition and 24 papers in Information Systems. Recurrent topics in Genlin Ji's work include Face and Expression Recognition (15 papers), Brain Tumor Detection and Classification (15 papers) and Data Management and Algorithms (15 papers). Genlin Ji is often cited by papers focused on Face and Expression Recognition (15 papers), Brain Tumor Detection and Classification (15 papers) and Data Management and Algorithms (15 papers). Genlin Ji collaborates with scholars based in China, United States and United Kingdom. Genlin Ji's co-authors include Yudong Zhang, Shuihua Wang‎, Zhengchao Dong, Preetha Phillips, Jiquan Yang, Jiquan Yang, Jian Wu, Qiong Wang, Chun-Mei Feng and Ling Wei and has published in prestigious journals such as Bioinformatics, Scientific Reports and Expert Systems with Applications.

In The Last Decade

Genlin Ji

134 papers receiving 3.9k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

A Comprehensive Survey on Particle Swarm Optimization Algorithm and Its Applications

2015 817 citations Genlin Ji et al. profile →
Binary PSO with mutation operator for feature selection using decision tree applied to spam detection

2014 344 citations Genlin Ji et al. Knowledge-Based Systems profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Genlin Ji China	28	1.3k	1.1k	999	429	302	145	4.0k
Preetha Phillips United States	34	1.3k 1.0×	1.4k 1.2×	1.3k 1.3×	456 1.1×	322 1.1×	58	4.0k
Lenan Wu China	35	1.4k 1.1×	1.2k 1.0×	881 0.9×	358 0.8×	218 0.7×	244	5.2k
Shuyuan Yang China	46	2.0k 1.5×	4.2k 3.8×	357 0.4×	642 1.5×	129 0.4×	432	9.4k
Kemal Polat Türkiye	46	2.9k 2.2×	1.3k 1.2×	388 0.4×	1.0k 2.4×	91 0.3×	239	7.9k
Jun Wang China	37	2.5k 1.9×	1.9k 1.7×	233 0.2×	638 1.5×	73 0.2×	327	6.5k
Heng-Da Cheng United States	38	2.6k 2.0×	3.6k 3.3×	292 0.3×	406 0.9×	168 0.6×	147	6.9k
Yanhui Guo United States	32	983 0.7×	1.3k 1.2×	232 0.2×	289 0.7×	125 0.4×	140	3.4k
M. Tanveer India	38	2.5k 1.8×	1.9k 1.7×	791 0.8×	226 0.5×	26 0.1×	185	5.0k
Nor Ashidi Mat Isa Malaysia	42	2.0k 1.5×	2.8k 2.5×	152 0.2×	311 0.7×	103 0.3×	229	6.1k
Shitong Wang China	44	3.9k 2.9×	2.4k 2.2×	208 0.2×	283 0.7×	130 0.4×	406	6.9k

Countries citing papers authored by Genlin Ji

Since Specialization

Citations

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

Fields of papers citing papers by Genlin Ji

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Genlin Ji

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Yang, Xichen, et al.. (2025). Underwater image quality assessment method via the fusion of visual and structural information. Signal Processing Image Communication. 136. 117285–117285.

2.

Yang, Xichen, et al.. (2025). Applying usability assessment method for surveillance video anomaly detection with multiple distortion. Journal of Visual Communication and Image Representation. 108. 104417–104417.

3.

Chen, Sheng, et al.. (2024). Label enhancement via manifold approximation and projection with graph convolutional network. Pattern Recognition. 152. 110447–110447. 5 indexed citations

4.

Zhang, Jiaxi, et al.. (2024). Efficient Representation Learning for Generalized Category Discovery. Knowledge-Based Systems. 300. 112214–112214. 1 indexed citations

5.

Ji, Genlin, et al.. (2023). Retraining Generative Adversarial Autoencoder for Video Anomaly Detection. 63–68.

6.

Liu, Cun, et al.. (2023). Human-centric multimodal fusion network for robust action recognition. Expert Systems with Applications. 239. 122314–122314. 19 indexed citations

7.

Liu, Richen, Hailong Wang, Chuyu Zhang, et al.. (2021). Narrative scientific data visualization in an immersive environment. Bioinformatics. 37(14). 2033–2041. 15 indexed citations

8.

Ji, Genlin, et al.. (2021). Collective periodic pattern discovery for understanding human mobility. Cluster Computing. 24(1). 141–157. 4 indexed citations

9.

Chen, Sheng, et al.. (2021). A Novel Probabilistic Label Enhancement Algorithm for Multi-Label Distribution Learning. IEEE Transactions on Knowledge and Data Engineering. 34(11). 5098–5113. 9 indexed citations

10.

Li-ming, Shen, et al.. (2020). Domain-Specific Language Techniques for Visual Computing: A Comprehensive Study. Archives of Computational Methods in Engineering. 28(4). 3113–3134. 16 indexed citations

11.

Chen, Sheng, et al.. (2020). Multilabel Distribution Learning Based on Multioutput Regression and Manifold Learning. IEEE Transactions on Cybernetics. 52(6). 5064–5078. 16 indexed citations

12.

Liu, Richen, et al.. (2019). Domain‐specific visualization system based on automatic multiseed recommendations: Extracting stratigraphic structures. Software Practice and Experience. 50(2). 98–115. 5 indexed citations

13.

Zhou, Xingxing, Haiping Zhang, Genlin Ji, & Guoan Tang. (2019). A Multi-Density Clustering Algorithm Based on Similarity for Dataset With Density Variation. IEEE Access. 7. 186004–186016. 3 indexed citations

14.

Ji, Genlin. (2009). A Spatial Clustering Algorithm Based on Intersection Relation for GML Data. Journal of Guangxi Normal University. 2 indexed citations

15.

Ji, Genlin. (2005). Image Retrieval System Based on Weighted Color Histogram and Color Pairs.

16.

Dai, Nan & Genlin Ji. (2005). Research and Implementation of ID3 Based on Distributed Database System. 1 indexed citations

17.

Ji, Genlin, et al.. (2005). Study on outlier mining approaches. Information technology newsletter.

18.

Wu, Zhifeng & Genlin Ji. (2005). Attribute reduction and rule extraction algorithms based on decision matrices. Jisuanji gongcheng. 1 indexed citations

19.

Ji, Genlin. (2004). The Study on Decision Tree Classification Techniques. Jisuanji gongcheng. 4 indexed citations

20.

Ji, Genlin. (2004). A Knowledge Reduction Method Based on Niche Genetic Algorithm. Jisuanji gongcheng. 3 indexed citations

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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