Bin Fu

54 papers receiving 1.2k citations

Bin Fu's Hit Papers

Deep & Cross Network for Ad Click Predictions 2017 · 641 citations
6410+3+6Years since publication200400600

Peers

Bin Fu
Comparison fields: 5 of 99
  • Information Systems 553
  • Artificial Intelligence 470
  • Computer Vision and Pattern Recognition 294
  • Computer Networks and Communications 270
  • Earth-Surface Processes 72
Replace Sulaiman Khan with:
Sulaiman Khan Pakistan
Jyotsna Kumar Mandal India
George E. Tsekouras Greece
Bernady O. Apduhan Japan
Sokol Kosta Denmark
Ling Tian China
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Yongquan Liang China
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Citations per year

Countries citing papers authored by Bin Fu

Since Specialization
Citations

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

Fields of papers citing papers by Bin Fu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 60 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Deep & Cross Network for Ad Click Predictions
Hit paper breakdown →
2017641
2 202157
3 201854
4 201744
5 202343
6 201838
7 202033
8 201332
9 202025
10 201725
11 200817
12 202017
13 201611
14 201811
15 200710
16 200810
17 201410
18 201710
19 201510
20 201110

About Bin Fu

Bin Fu is a scholar working on Computer Networks and Communications, Oceanography, Earth-Surface Processes, Artificial Intelligence and Cardiology and Cardiovascular Medicine, having authored 60 papers that have together received 1.2k indexed citations. Recurring topics across this work include Ocean Waves and Remote Sensing (15 papers), Coastal and Marine Dynamics (11 papers), ECG Monitoring and Analysis (9 papers), EEG and Brain-Computer Interfaces (7 papers), Oceanographic and Atmospheric Processes (7 papers), Remote Sensing and LiDAR Applications (6 papers), Text and Document Classification Technologies (5 papers) and Non-Invasive Vital Sign Monitoring (4 papers). The work is most often cited by research in Information Systems (553 citations), Artificial Intelligence (470 citations), Computer Vision and Pattern Recognition (294 citations), Computer Networks and Communications (270 citations) and Earth-Surface Processes (72 citations). Bin Fu has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Mingliang Wang, Ruoxi Wang, Gang Fu, Zhu Xiao, Renfa Li, Huaguo Zhang, Hongzhi Liu, Hongbo Jiang, Zhonghai Wu and Jilong Wang. Their work appears in journals such as International Journal of Remote Sensing, Engineering Applications of Artificial Intelligence, Journal of Systems Architecture, International Journal of Machine Learning and Cybernetics and Knowledge-Based Systems.

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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