Ji Feng

2.5k citations
22 papers · 1.6k indexed · 2 hit papers · h-index 10
Topics
Anomaly Detection Techniques and Applications (7 papers)Machine Learning and Data Classification (5 papers)Face and Expression Recognition (5 papers)

In The Last Decade

Ji Feng

21 papers receiving 1.6k citations

Hit Papers

Deep Forest: Towards An Alternative to Deep Neural Networks201720262020202320172018200400600

Peers

Ji Feng
Comparison fields: 5 of 146
  • Artificial Intelligence 806
  • Computer Vision and Pattern Recognition 375
  • Molecular Biology 147
  • Signal Processing 145
  • Information Systems 131
Replace Yifan Shi with:
Yifan Shi China
Gongbo Zhang United States
Abiodun M. Ikotun South Africa
Wenming Cao China
Juan Carlos Fernández Fernández Spain
B. Eswara Reddy India
Yan Pei Japan
Yujian Li China
John Berkowitz United States
Ji Feng relative to Yifan Shi China Yifan Shi's profile →
Citations per field
00.5×10×20×30.7×
Yifan Shi · 1×
Citations per year

Countries citing papers authored by Ji Feng

Since Specialization
Citations

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

Fields of papers citing papers by Ji Feng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ji Feng

This figure shows the co-authorship network connecting the top 25 collaborators of Ji Feng. A scholar is included among the top collaborators of Ji Feng 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 Ji Feng. Ji Feng 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 1
2 0
3 1
4 5
5 1
6 3
7 14
8 51
9 1
10
Multi-Layered Gradient Boosting Decision Trees
9
11 5
12
Deep forestbreakdown →
556
13
Deep MIML Network
34
14
Deep Forest: Towards An Alternative to Deep Neural Networksbreakdown →
613
15 181
16 17
17 122
18 2
19 12
20 3

About Ji Feng

Ji Feng is a scholar working on Signal Processing, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 22 papers that have together received 1.6k indexed citations. Recurring topics across this work include Anomaly Detection Techniques and Applications (7 papers), Machine Learning and Data Classification (5 papers) and Face and Expression Recognition (5 papers). The work is most often cited by research in Artificial Intelligence (806 citations), Computer Vision and Pattern Recognition (375 citations) and Signal Processing (145 citations). Ji Feng has collaborated with scholars based in China, Netherlands and Saudi Arabia. Frequent co-authors include Zhi‐Hua Zhou, Qingsheng Zhu, Jinlong Huang, Lijun Yang, Bin Fang, Chaochao Chen, Shougui Zhang, Yalin Zhang, Qi Yuan and Ziqi Liu. Their work appears in journals such as Expert Systems with Applications, IEEE Access and IEEE Transactions on Cybernetics.

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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026