Cheng-Yang Fu

2.1k total citations
10 papers, 129 citations indexed

About

Cheng-Yang Fu is a scholar working on Computer Vision and Pattern Recognition, Hardware and Architecture and Computer Networks and Communications. According to data from OpenAlex, Cheng-Yang Fu has authored 10 papers receiving a total of 129 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Computer Vision and Pattern Recognition, 5 papers in Hardware and Architecture and 4 papers in Computer Networks and Communications. Recurrent topics in Cheng-Yang Fu's work include Parallel Computing and Optimization Techniques (5 papers), Advanced Neural Network Applications (3 papers) and Embedded Systems Design Techniques (3 papers). Cheng-Yang Fu is often cited by papers focused on Parallel Computing and Optimization Techniques (5 papers), Advanced Neural Network Applications (3 papers) and Embedded Systems Design Techniques (3 papers). Cheng-Yang Fu collaborates with scholars based in Taiwan, United States and Israel. Cheng-Yang Fu's co-authors include James H. Anderson, Bryan C. Ward, Alexander Berg, F. Donelson Smith, Ren‐Song Tsay, Mohit Bansal, Joon Lee, Tamara L. Berg, Tsu-Jui Fu and Sean Bell and has published in prestigious journals such as ACM Transactions on Embedded Computing Systems, ACM Transactions on Design Automation of Electronic Systems and King Abdullah University of Science and Technology Repository (King Abdullah University of Science and Technology).

In The Last Decade

Cheng-Yang Fu

10 papers receiving 125 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Cheng-Yang Fu Taiwan	6	67	50	48	18	11	10	129
Patrick Carribault France	6	89 1.3×	77 1.5×	24 0.5×	28 1.6×	5 0.5×	19	123
Markku–Juhani O. Saarinen United Kingdom	6	25 0.4×	26 0.5×	49 1.0×	88 4.9×	15 1.4×	18	121
Norbert Pramstaller Austria	8	40 0.6×	20 0.4×	84 1.8×	101 5.6×	14 1.3×	15	130
Jaechul Sung South Korea	7	36 0.5×	16 0.3×	94 2.0×	124 6.9×	22 2.0×	39	139
Yasuhiro Ohtaki Japan	6	15 0.2×	42 0.8×	23 0.5×	33 1.8×	5 0.5×	18	93
Riadh Robbana Tunisia	6	15 0.2×	46 0.9×	10 0.2×	31 1.7×	13 1.2×	37	84
Gaël Thomas France	7	67 1.0×	91 1.8×	17 0.4×	47 2.6×	9 0.8×	21	138
Eric Senn France	8	108 1.6×	87 1.7×	9 0.2×	11 0.6×	10 0.9×	26	160
Ronny Van Keer Netherlands	6	29 0.4×	18 0.4×	80 1.7×	116 6.4×	16 1.5×	7	142
Maxime Chevalier-Boisvert Canada	6	31 0.5×	16 0.3×	18 0.4×	72 4.0×	7 0.6×	10	98

Countries citing papers authored by Cheng-Yang Fu

Since Specialization

Citations

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

Fields of papers citing papers by Cheng-Yang Fu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Cheng-Yang Fu

This figure shows the co-authorship network connecting the top 25 collaborators of Cheng-Yang Fu. A scholar is included among the top collaborators of Cheng-Yang Fu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Cheng-Yang Fu. Cheng-Yang Fu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

10 of 10 papers shown

1.

Gustafson, Laura, Nikhila Ravi, Quentin Duval, et al.. (2023). FACET: Fairness in Computer Vision Evaluation Benchmark. 20313–20325. 9 indexed citations

2.

Xu, Mengmeng, et al.. (2023). Where is my Wallet? Modeling Object Proposal Sets for Egocentric Visual Query Localization. King Abdullah University of Science and Technology Repository (King Abdullah University of Science and Technology). 2593–2603. 3 indexed citations

3.

Fu, Tsu-Jui, Licheng Yu, Ning Zhang, et al.. (2023). Tell Me What Happened: Unifying Text-guided Video Completion via Multimodal Masked Video Generation. 10681–10692. 16 indexed citations

4.

Fu, Cheng-Yang, Tamara L. Berg, & Alexander Berg. (2019). IMP: Instance Mask Projection for High Accuracy Semantic Segmentation of Things. 5177–5186. 9 indexed citations

5.

Fu, Cheng-Yang, Joon Lee, Mohit Bansal, & Alexander Berg. (2017). Video Highlight Prediction Using Audience Chat Reactions. 972–978. 20 indexed citations

6.

Ward, Bryan C., et al.. (2016). Attacking the One-Out-Of-m Multicore Problem by Combining Hardware Management with Mixed-Criticality Provisioning. 48 indexed citations

7.

Fu, Cheng-Yang, et al.. (2013). A distributed timing synchronization technique for parallel multi-core instruction-set simulation. ACM Transactions on Embedded Computing Systems. 12(1s). 1–24. 4 indexed citations

8.

Fu, Cheng-Yang, et al.. (2012). An Extended SystemC Framework for Efficient HW/SW Co-Simulation. ACM Transactions on Design Automation of Electronic Systems. 17(2). 1–16. 1 indexed citations

9.

Fu, Cheng-Yang, et al.. (2011). A high-parallelism distributed scheduling mechanism for multi-core instruction-set simulation. 339–344. 4 indexed citations

10.

Fu, Cheng-Yang, et al.. (2009). An effective synchronization approach for fast and accurate multi-core instruction-set simulation. 197–204. 15 indexed citations

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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