Hao Zhu

1.6k citations
43 papers · 758 indexed · h-index 13

Hao Zhu

40 papers receiving 734 citations

Peers

Hao Zhu
Comparison fields: 5 of 73
  • Computer Vision and Pattern Recognition 271
  • Artificial Intelligence 417
  • Management Science and Operations Research 150
  • Media Technology 51
  • Human-Computer Interaction 24
Replace Ethan Perez with:
Ethan Perez United States
Alexander G. Ororbia United States
Yihong Gong United States
Amarnag Subramanya United States
Yong Zhu China
Shoou-I Yu United States
Eric Garcia United States
Tanuja Sarode India
Catherine Wah United States
Yulei Niu China
Hao Zhu relative to Ethan Perez United States Ethan Perez's profile →
Citations per field
00.5×8.3×
Ethan Perez · 1×
Citations per year

Countries citing papers authored by Hao Zhu

Since Specialization
Citations

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

Fields of papers citing papers by Hao Zhu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20250
2 20251
3 20241
4 20241
5 202412
6 20241
7 20234
8 20234
9 20238
10 20229
11 20215
12 202010
13 2019143
14 20197
15 201815
16 20171
17 20163
18
Stimulatory effects of wheat (Triticum aestivum L.) on seed germination of Orobanche minor Sm
20129
19 201115
20
A Recognition Algorithm for 2D Geometric Similarity of Blanking Part
20050

About Hao Zhu

Hao Zhu is a scholar working on Media Technology, Computer Vision and Pattern Recognition and Computer Graphics and Computer-Aided Design, having authored 43 papers that have together received 758 indexed citations. Recurring topics across this work include Advanced Vision and Imaging (17 papers), Image Processing Techniques and Applications (9 papers), Topic Modeling (7 papers), Image Enhancement Techniques (7 papers), Optical measurement and interference techniques (5 papers), Natural Language Processing Techniques (4 papers), Advanced Image Processing Techniques (4 papers) and Neuroscience and Neural Engineering (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (271 citations), Artificial Intelligence (417 citations) and Management Science and Operations Research (150 citations). Hao Zhu has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Maosong Sun, Zhiyuan Liu, Ruobing Xie, Qing Wang, Jingyi Yu, Tianyu Gao, Jie Zhou, Xu Han, Qing Wang and Bin He. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing and IEEE Transactions on Medical Imaging.

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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