Hongfa Wang

2.4k citations
105 papers · 1.4k · h-index 21

Impact in

Papers in

    • Marine Bivalve and Aquaculture Studies 20
    • Marine and fisheries research 15
    • Flood Risk Assessment and Management 9
    • Marine Biology and Ecology Research 25
    • Marine and coastal plant biology 9

Hongfa Wang

99 papers receiving 1.4k citations

Peers

Hongfa Wang
Comparison fields: 5 of 145
  • Computer Vision and Pattern Recognition 389
  • Oceanography 200
  • Media Technology 129
  • Global and Planetary Change 231
  • Parasitology 58
Replace Takahiro Kikuchi with:
Takahiro Kikuchi Japan
Andreas Schmidt Germany
William Lang United States
Patrick A. Kelly United States
Xuemin Cheng China
Véronique Perrier France
Yueting Zhang China
Fang Chen China
A. Ruiz-Jimeno Spain
Guang Li China
Hongfa Wang relative to Takahiro Kikuchi Japan Takahiro Kikuchi's profile →
Citations per field
00.5×10×16.2×
Takahiro Kikuchi · 1×
Citations per year

Countries citing papers authored by Hongfa Wang

Since Specialization
Citations

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

Fields of papers citing papers by Hongfa Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 105 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020144
2 2021124
3 202284
4 202171
5 200751
6 202348
7 200846
8 202234
9 202033
10 202432
11 202429
12 202128
13 202128
14 201524
15 201424
16 201723
17 202022
18 202021
19 201821
20 202120

About Hongfa Wang

Hongfa Wang is a scholar working on Global and Planetary Change, Oceanography, Computer Vision and Pattern Recognition, Organic Chemistry and Artificial Intelligence, having authored 105 papers that have together received 1.4k indexed citations. Recurring topics across this work include Marine Biology and Ecology Research (25 papers), Marine Bivalve and Aquaculture Studies (20 papers), Marine and fisheries research (15 papers), Marine and coastal plant biology (9 papers), Flood Risk Assessment and Management (9 papers), Advanced Image and Video Retrieval Techniques (7 papers), Multimodal Machine Learning Applications (6 papers) and Hydrological Forecasting Using AI (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (389 citations), Oceanography (200 citations), Media Technology (129 citations), Global and Planetary Change (231 citations) and Parasitology (58 citations). Hongfa Wang has collaborated with scholars based in China, Hong Kong and Singapore. Frequent co-authors include Weiwei Zi, Xinzheng Li, Qinglong Zhang, Xu-Cheng Yin, Xiaobin Zhu, Chun Yang, Shi-Xue Zhang, Baolin Zhang, Yong Xu and Ruiyuan Zhang. Their work appears in journals such as Marine Pollution Bulletin, Water Resources Management, IEEE Transactions on Image Processing, RSC Advances and IEEE Transactions on Pattern Analysis and Machine Intelligence.

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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