Saiji Fu

32 total papers · 454 total citations
27 papers, 275 citations indexed

About

Saiji Fu is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Electrical and Electronic Engineering. According to data from OpenAlex, Saiji Fu has authored 27 papers receiving a total of 275 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Artificial Intelligence, 14 papers in Computer Vision and Pattern Recognition and 3 papers in Electrical and Electronic Engineering. Recurrent topics in Saiji Fu's work include Face and Expression Recognition (11 papers), Imbalanced Data Classification Techniques (8 papers) and Machine Learning and ELM (7 papers). Saiji Fu is often cited by papers focused on Face and Expression Recognition (11 papers), Imbalanced Data Classification Techniques (8 papers) and Machine Learning and ELM (7 papers). Saiji Fu collaborates with scholars based in China and United Kingdom. Saiji Fu's co-authors include Yingjie Tian, Jingjing Tang, Xiaotong Yu, Long Tang, Kun Zhao, Xiaohui Liu, Xiaoxiao Wang, Shulin Lan, Minghao Liu and Yu Sun and has published in prestigious journals such as European Journal of Operational Research, Expert Systems with Applications and IEEE Access.

In The Last Decade

Saiji Fu

24 papers receiving 268 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Saiji Fu	172	104	40	25	24	27	275
Anurag Sharma	146 0.8×	35 0.3×	43 1.1×	20 0.8×	12 0.5×	35	303
Naresh Manwani	211 1.2×	64 0.6×	18 0.5×	14 0.6×	26 1.1×	14	268
Kan Chen	163 0.9×	148 1.4×	25 0.6×	17 0.7×	11 0.5×	28	321
Yunfeng Zhao	107 0.6×	36 0.3×	40 1.0×	10 0.4×	7 0.3×	25	281
Rehab F. Abdel‐Kader	101 0.6×	77 0.7×	30 0.8×	22 0.9×	19 0.8×	32	296
Chao Yu	172 1.0×	34 0.3×	24 0.6×	57 2.3×	32 1.3×	25	322
Iztok Fister	146 0.8×	39 0.4×	22 0.6×	25 1.0×	40 1.7×	32	321
Li Li	106 0.6×	58 0.6×	20 0.5×	20 0.8×	5 0.2×	21	255
Santos Kumar Baliarsingh	177 1.0×	62 0.6×	22 0.6×	20 0.8×	15 0.6×	27	297
Jayashree Piri	170 1.0×	51 0.5×	18 0.5×	14 0.6×	14 0.6×	21	317

Countries citing papers authored by Saiji Fu

Since Specialization

Citations

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

Fields of papers citing papers by Saiji Fu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Saiji Fu

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

All Works

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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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