Hongwei Ge

2.4k citations
140 papers · 1.6k indexed · h-index 20

Hongwei Ge

124 papers receiving 1.5k citations

Peers

Hongwei Ge
Comparison fields: 5 of 127
  • Artificial Intelligence 690
  • Computer Vision and Pattern Recognition 365
  • Industrial and Manufacturing Engineering 165
  • Computational Theory and Mathematics 257
  • Control and Systems Engineering 332
Replace Michalis Mavrovouniotis with:
Michalis Mavrovouniotis United Kingdom
Genke Yang China
Fang Tang China
Suining He United States
Yiu-Wing Leung Hong Kong
Xiao Zhang China
Mohammed El-Abd Kuwait
Michael G. Kay United States
Yinan Guo China
Hongwei Ge relative to Michalis Mavrovouniotis United Kingdom Michalis Mavrovouniotis's profile →
Citations per field
00.5×1.5×
Michalis Mavrovouniotis · 1×
Citations per year

Countries citing papers authored by Hongwei Ge

Since Specialization
Citations

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

Fields of papers citing papers by Hongwei Ge

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Hongwei Ge, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Hongwei Ge Line = papers co-authored together Hongwei Ge links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20251
2 20250
3 20242
4 20240
5 20248
6 20242
7 20232
8 20234
9 20231
10 20238
11 202315
12 20237
13 201992
14
An Interactive Many Objective Evolutionary Algorithm with Cascade Clustering and Reference Point Incremental Learning.
20181
15 20161
16
Particle swarm optimization algorithm with firefly behavior and Levy flight
20162
17
Particle Swarm Optimization Algorithm Based on Multi-swarm and Multi-model Cooperative Evolution
20130
18
Edges Immunization Strategy in Scale-free Network
20113
19
New hybrid particle swarm optimization
20118
20
Rich-club phenomenon based search immunization
20101

About Hongwei Ge

Hongwei Ge is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Media Technology, having authored 140 papers that have together received 1.6k indexed citations. Recurring topics across this work include Metaheuristic Optimization Algorithms Research (26 papers), Evolutionary Algorithms and Applications (16 papers), Video Surveillance and Tracking Methods (16 papers), Advanced Multi-Objective Optimization Algorithms (14 papers), Human Pose and Action Recognition (11 papers), Advanced Image Processing Techniques (9 papers), Reinforcement Learning in Robotics (7 papers) and Neural Networks and Applications (7 papers). The work is most often cited by research in Artificial Intelligence (690 citations), Computer Vision and Pattern Recognition (365 citations) and Industrial and Manufacturing Engineering (165 citations). Hongwei Ge has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Liang Sun, Yanchun Liang, Feng Qian, Chunguo Wu, Guozhen Tan, Yaqing Hou, Liang Sun, Yanchun Liang, Wenli Du and Heow Pueh Lee. Their work appears in journals such as PLoS ONE, Automatica and IEEE Transactions on Image Processing.

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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