Sugata Munshi

1.9k total citations
67 papers, 1.4k citations indexed

About

Sugata Munshi is a scholar working on Biomedical Engineering, Computer Vision and Pattern Recognition and Electrical and Electronic Engineering. According to data from OpenAlex, Sugata Munshi has authored 67 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Biomedical Engineering, 18 papers in Computer Vision and Pattern Recognition and 17 papers in Electrical and Electronic Engineering. Recurrent topics in Sugata Munshi's work include Sensor Technology and Measurement Systems (11 papers), Cutaneous Melanoma Detection and Management (10 papers) and Advanced Sensor Technologies Research (9 papers). Sugata Munshi is often cited by papers focused on Sensor Technology and Measurement Systems (11 papers), Cutaneous Melanoma Detection and Management (10 papers) and Advanced Sensor Technologies Research (9 papers). Sugata Munshi collaborates with scholars based in India and United Kingdom. Sugata Munshi's co-authors include Debangshu Dey, Amitava Chatterjee, Saptarshi Chatterjee, Biswendu Chatterjee, S. Chakravorti, Biswarup Ganguly, Sovan Dalai, Biswajit Bhattacharyya, Subrata Biswas and Sabyasachi Bandyopadhyay and has published in prestigious journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications and IEEE Transactions on Intelligent Transportation Systems.

In The Last Decade

Sugata Munshi

65 papers receiving 1.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sugata Munshi India 21 366 311 285 265 221 67 1.4k
Debangshu Dey India 25 701 1.9× 311 1.0× 290 1.0× 345 1.3× 211 1.0× 111 2.0k
Sudipta Mukhopadhyay India 27 502 1.4× 234 0.8× 436 1.5× 514 1.9× 745 3.4× 133 2.8k
Seong‐Eun Kim South Korea 24 133 0.4× 381 1.2× 80 0.3× 199 0.8× 114 0.5× 107 1.7k
Saeed Mian Qaisar Saudi Arabia 25 517 1.4× 512 1.6× 299 1.0× 262 1.0× 156 0.7× 172 2.0k
Kai Ma China 27 157 0.4× 593 1.9× 717 2.5× 317 1.2× 730 3.3× 118 2.5k
Jingwei Too Malaysia 25 150 0.4× 299 1.0× 830 2.9× 382 1.4× 248 1.1× 41 1.7k
Abdul Rahim Abdullah Malaysia 21 672 1.8× 243 0.8× 480 1.7× 408 1.5× 244 1.1× 173 1.9k
Yusuke Tamura Japan 23 73 0.2× 181 0.6× 122 0.4× 330 1.2× 505 2.3× 166 2.1k
Rajesh Mehra India 16 627 1.7× 44 0.1× 454 1.6× 195 0.7× 331 1.5× 164 1.4k
Julius Georgiou Cyprus 21 999 2.7× 776 2.5× 177 0.6× 585 2.2× 61 0.3× 139 2.3k

Countries citing papers authored by Sugata Munshi

Since Specialization
Citations

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

Fields of papers citing papers by Sugata Munshi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sugata Munshi

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

All Works

20 of 20 papers shown
1.
Ganguly, Biswarup, Debangshu Dey, & Sugata Munshi. (2025). An Attention Deep Learning Framework-Based Drowsiness Detection Model for Intelligent Transportation System. IEEE Transactions on Intelligent Transportation Systems. 26(4). 4517–4527. 1 indexed citations
2.
Dey, Debangshu, et al.. (2023). Detection of Simultaneous Bearing Faults Fusing Cross Correlation With Multikernel SVM. IEEE Sensors Journal. 23(13). 14418–14427. 13 indexed citations
3.
Ganguly, Biswarup, Debangshu Dey, & Sugata Munshi. (2022). An Unsupervised Learning Approach for Road Anomaly Segmentation Using RGB-D Sensor for Advanced Driver Assistance System. IEEE Transactions on Intelligent Transportation Systems. 23(10). 19042–19053. 11 indexed citations
4.
Ganguly, Biswarup, Debangshu Dey, & Sugata Munshi. (2022). An Integrated System for Drivers’ Drowsiness Detection Using Deep Learning Frameworks. 55–59. 5 indexed citations
5.
6.
Ganguly, Biswarup, et al.. (2021). Single Image Haze Removal With Haze Map Optimization for Various Haze Concentrations. IEEE Transactions on Circuits and Systems for Video Technology. 32(1). 286–301. 21 indexed citations
7.
Ganguly, Biswarup, Debangshu Dey, & Sugata Munshi. (2021). Image Visibility Filter-Based Interpretable Deep Learning Framework for Skin Lesion Diagnosis. IEEE Transactions on Industrial Informatics. 18(8). 5138–5147. 13 indexed citations
8.
Chatterjee, Saptarshi, et al.. (2020). Dermatological expert system implementing the ABCD rule of dermoscopy for skin disease identification. Expert Systems with Applications. 167. 114204–114204. 21 indexed citations
9.
Chatterjee, Saptarshi, et al.. (2020). An adaptive morphology based segmentation technique for lung nodule detection in thoracic CT image. Computer Methods and Programs in Biomedicine. 197. 105720–105720. 30 indexed citations
10.
Bhattacharyya, Biswajit, et al.. (2019). A Combination of Astable Multivibrator and Microcontroller for Thermistor-Based Temperature Measurement Over Internet. IEEE Sensors Journal. 19(9). 3252–3259. 14 indexed citations
11.
Chatterjee, Saptarshi, Debangshu Dey, & Sugata Munshi. (2019). Integration of morphological preprocessing and fractal based feature extraction with recursive feature elimination for skin lesion types classification. Computer Methods and Programs in Biomedicine. 178. 201–218. 91 indexed citations
12.
13.
Jana, S., et al.. (2017). A Log Amplifier Based Linearization Scheme for Thermocouples. SHILAP Revista de lepidopterología. 5 indexed citations
14.
Dey, Debangshu, et al.. (2017). Obstructive sleep apnoea detection using convolutional neural network based deep learning framework. Biomedical Engineering Letters. 8(1). 95–100. 104 indexed citations
15.
Bandyopadhyay, Sabyasachi, Arnab Das, Anwesha Mukherjee, et al.. (2015). A Linearization Scheme for Thermistor-Based Sensing in Biomedical Studies. IEEE Sensors Journal. 16(3). 603–609. 31 indexed citations
16.
17.
Dey, Debangshu, et al.. (2013). Linearization of NTC Thermistor Characteristic Using Op-Amp Based Inverting Amplifier. IEEE Sensors Journal. 13(12). 4621–4626. 37 indexed citations
18.
Djokic, Sasa, et al.. (2007). Analytical Modeling of Adjustable Speed Drive Load for Power System Studies. 1899–1904. 7 indexed citations
19.
Chatterjee, Amitava & Sugata Munshi. (2005). Application of ANN to thermistor based temperature measurement systems. International Journal of Knowledge-based and Intelligent Engineering Systems. 9(3). 231–237. 4 indexed citations
20.
Chatterjee, Amitava, et al.. (2004). A new self-tuned PID-type fuzzy controller as a combination of two-term controllers. ISA Transactions. 43(3). 413–426. 13 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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