Flood Sung

5.3k total citations
3 papers, 23 citations indexed

About

Flood Sung is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Ocean Engineering. According to data from OpenAlex, Flood Sung has authored 3 papers receiving a total of 23 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Artificial Intelligence, 1 paper in Computer Vision and Pattern Recognition and 1 paper in Ocean Engineering. Recurrent topics in Flood Sung's work include Domain Adaptation and Few-Shot Learning (3 papers), Geophysical Methods and Applications (1 paper) and Multimodal Machine Learning Applications (1 paper). Flood Sung is often cited by papers focused on Domain Adaptation and Few-Shot Learning (3 papers), Geophysical Methods and Applications (1 paper) and Multimodal Machine Learning Applications (1 paper). Flood Sung collaborates with scholars based in United Kingdom and China. Flood Sung's co-authors include Yongxin Yang, Timothy M. Hospedales, Xueting Zhang, Jian Luan, Shuo Shang, Xiuying Chen and Xiaoqing Zhang and has published in prestigious journals such as arXiv (Cornell University).

In The Last Decade

Flood Sung

3 papers receiving 23 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Flood Sung United Kingdom	2	20	13	4	3	3	3	23
Zhengyuan Zhou China	3	18 0.9×	18 1.4×	4 1.0×	3 1.0×	1 0.3×	6	30
Ruixuan Luo China	4	15 0.8×	21 1.6×	5 1.3×	2 0.7×	6 2.0×	5	33
Rafael Felix Australia	4	26 1.3×	18 1.4×	5 1.3×			4	37
Shahaf E. Finder Israel	2	19 0.9×	13 1.0×		2 0.7×	2 0.7×	3	35
Łukasz Lew United States	2	27 1.4×	14 1.1×	3 0.8×			3	39
Gaurav Manek Singapore	2	10 0.5×	14 1.1×	3 0.8×		3 1.0×	2	31
Nontawat Charoenphakdee Japan	4	47 2.4×	30 2.3×	4 1.0×	1 0.3×	3 1.0×	7	56
Yuefei Wang China	4	22 1.1×	34 2.6×	3 0.8×		2 0.7×	11	45
Chen-Yu Lee Taiwan	1	28 1.4×	28 2.2×	1 0.3×	2 0.7×	3 1.0×	2	55
Shoumeng Qiu China	4	9 0.5×	26 2.0×	14 3.5×	3 1.0×	3 1.0×	11	41

Countries citing papers authored by Flood Sung

Since Specialization

Citations

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

Fields of papers citing papers by Flood Sung

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Flood Sung

This figure shows the co-authorship network connecting the top 25 collaborators of Flood Sung. A scholar is included among the top collaborators of Flood Sung 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 Flood Sung. Flood Sung is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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3 of 3 papers shown

1.

Zhang, Xiaoqing, et al.. (2025). More is not always better? Enhancing Many-Shot In-Context Learning with Differentiated and Reweighting Objectives. 30539–30552. 1 indexed citations

2.

Zhang, Xueting, et al.. (2020). RelationNet2: Deep Comparison Network for Few-Shot Learning. 1–8. 12 indexed citations

3.

Sung, Flood, et al.. (2018). Deep Comparison: Relation Columns for Few-Shot Learning.. arXiv (Cornell University). 10 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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