Hao Ren

453 citations
31 papers · 267 · h-index 7

Impact in

Papers in

Hao Ren

27 papers receiving 262 citations

Peers

Hao Ren
Comparison fields: 5 of 53
  • Computer Vision and Pattern Recognition 153
  • Computer Networks and Communications 24
  • Artificial Intelligence 33
  • Health Informatics 2
  • Geology 5
Replace Chandrakala Arya with:
Chandrakala Arya India
Harini Sriraman India
Oussama Benrhouma Saudi Arabia
G. Sreenu India
Huaizheng Zhang Singapore
Saman Iftikhar Pakistan
Amran Bhuiyan Canada
Eduardo Silva Alvarado Spain
Osama Hosameldeen Egypt
Hao Ren relative to Chandrakala Arya India Chandrakala Arya's profile →
Citations per field
00.5×2×2.8×
Chandrakala Arya · 1×
Citations per year

Countries citing papers authored by Hao Ren

Since Specialization
Citations

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

Fields of papers citing papers by Hao Ren

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Hao Ren, 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 Hao Ren Line = papers co-authored together Hao Ren links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 31 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201971
2 202357
3 202223
4 202319
5 201914
6 200610
7 202210
8 20177
9 20237
10 20225
11 20235
12 20074
13 20084
14 20254
15
Smart aging system
20193
16 20243
17 20253
18 20152
19 20222
20 20222

About Hao Ren

Hao Ren is a scholar working on Computer Vision and Pattern Recognition, Computer Networks and Communications, Geology, Computational Mechanics and Artificial Intelligence, having authored 31 papers that have together received 267 indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (5 papers), Image Enhancement Techniques (4 papers), 3D Shape Modeling and Analysis (3 papers), Peer-to-Peer Network Technologies (3 papers), Image Retrieval and Classification Techniques (3 papers), Reinforcement Learning in Robotics (2 papers), Human Pose and Action Recognition (2 papers) and 3D Surveying and Cultural Heritage (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (153 citations), Computer Networks and Communications (24 citations), Artificial Intelligence (33 citations), Health Informatics (2 citations) and Geology (5 citations). Hao Ren has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Hong Lu, Hongwei Wang, Prosanta Gope, Ziqiang Zheng, Sharnil Pandya, Subhas Chandra Mukhopadhyay, Saeed Akbarzadeh, Wei Chen, Hemant Ghayvat and Muhammad Azam Awais. Their work appears in journals such as IEEE Transactions on Circuits and Systems for Video Technology, Sustainability, Sensors, Computers and Electronics in Agriculture and International Journal of Mechanical Sciences.

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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