Kuhu Pal

1.5k total citations · 1 hit paper
11 papers, 1.1k citations indexed

About

Kuhu Pal is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Signal Processing. According to data from OpenAlex, Kuhu Pal has authored 11 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Artificial Intelligence, 6 papers in Computational Theory and Mathematics and 2 papers in Signal Processing. Recurrent topics in Kuhu Pal's work include Fuzzy Logic and Control Systems (8 papers), Rough Sets and Fuzzy Logic (6 papers) and Neural Networks and Applications (5 papers). Kuhu Pal is often cited by papers focused on Fuzzy Logic and Control Systems (8 papers), Rough Sets and Fuzzy Logic (6 papers) and Neural Networks and Applications (5 papers). Kuhu Pal collaborates with scholars based in India, United States and Germany. Kuhu Pal's co-authors include Nikhil R. Pal, James C. Bezdek, James M. Keller, Subhash Bagui, Sikha Bagui, Thomas A. Runkler and S. Chakraborty and has published in prestigious journals such as Pattern Recognition, IEEE Transactions on Fuzzy Systems and Neural Networks.

In The Last Decade

Kuhu Pal

11 papers receiving 1.0k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

A possibilistic fuzzy c-means clustering algorithm

2005 917 citations Nikhil R. Pal, Kuhu Pal et al. IEEE Transactions on Fuzzy Systems profile →

Peers

Kuhu Pal

AI

CVPR

MT

SP

CTM

Raghu Krisnapuram United States

Katsuhiro Honda Japan

H. Ichihashi Japan

Wojciech Siedlecki United States

Lingfeng Niu China

Frank Chung-Hoon Rhee South Korea

Malay K. Pakhira India

Masao Mukaidono Japan

Petr Somol Czechia

Julio López Chile

Raghu Krisnapuram United States

Kuhu Pal

544 ×0.8

AI

406 ×0.9

CVPR

116 ×0.9

MT

166 ×1.3

SP

104 ×0.9

CTM

Citations per year, relative to Kuhu Pal Kuhu Pal (= 1×) peers Raghu Krisnapuram

Countries citing papers authored by Kuhu Pal

Since Specialization

Citations

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

Fields of papers citing papers by Kuhu Pal

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kuhu Pal

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

All Works

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11 of 11 papers shown

1.

Pal, Nikhil R., Kuhu Pal, James M. Keller, & James C. Bezdek. (2005). A possibilistic fuzzy c-means clustering algorithm. IEEE Transactions on Fuzzy Systems. 13(4). 517–530. 917 indexed citations breakdown →

2.

Pal, Kuhu, Nikhil R. Pal, James M. Keller, & James C. Bezdek. (2005). Relational mountain (density) clustering method and web log analysis. International Journal of Intelligent Systems. 20(3). 375–392. 2 indexed citations

3.

Pal, Nikhil R., Kuhu Pal, James M. Keller, & James C. Bezdek. (2005). A new hybrid c-means clustering model. 1. 179–184. 27 indexed citations

4.

Chakraborty, S., Kuhu Pal, & Nikhil R. Pal. (2002). A neuro-fuzzy framework for inferencing. Neural Networks. 15(2). 247–261. 6 indexed citations

5.

Pal, Kuhu, et al.. (2002). Some issues in system identification using clustering. Proceedings of International Conference on Neural Networks (ICNN'97). 4. 2524–2529. 27 indexed citations

6.

Bagui, Subhash, Sikha Bagui, Kuhu Pal, & Nikhil R. Pal. (2002). Breast cancer detection using rank nearest neighbor classification rules. Pattern Recognition. 36(1). 25–34. 68 indexed citations

7.

Pal, Nikhil R. & Kuhu Pal. (1999). Handling of inconsistent rules with an extended model of fuzzy reasoning. Journal of Intelligent & Fuzzy Systems. 7(1). 55–73. 30 indexed citations

8.

Pal, Kuhu & Nikhil R. Pal. (1999). A neuro-fuzzy system for inferencing. International Journal of Intelligent Systems. 14(11). 1155–1182. 6 indexed citations

9.

Pal, Kuhu & Nikhil R. Pal. (1998). Learning of rule importance for fuzzy controllers to deal with inconsistent rules and for rule elimination. Control and Cybernetics. 27(4). 521–543. 1 indexed citations

10.

Pal, Kuhu, Nikhil R. Pal, & James M. Keller. (1998). Some neural net realizations of fuzzy reasoning. International Journal of Intelligent Systems. 13(9). 859–886. 8 indexed citations

11.

Pal, Kuhu, Nikhil R. Pal, & James M. Keller. (1998). Some neural net realizations of fuzzy reasoning. International Journal of Intelligent Systems. 13(9). 859–886. 4 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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