Shankar Thawkar

714 total citations
23 papers, 511 citations indexed

About

Shankar Thawkar is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Computer Vision and Pattern Recognition. According to data from OpenAlex, Shankar Thawkar has authored 23 papers receiving a total of 511 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 9 papers in Radiology, Nuclear Medicine and Imaging and 8 papers in Computer Vision and Pattern Recognition. Recurrent topics in Shankar Thawkar's work include AI in cancer detection (9 papers), Retinal Imaging and Analysis (7 papers) and Gene expression and cancer classification (5 papers). Shankar Thawkar is often cited by papers focused on AI in cancer detection (9 papers), Retinal Imaging and Analysis (7 papers) and Gene expression and cancer classification (5 papers). Shankar Thawkar collaborates with scholars based in India. Shankar Thawkar's co-authors include Munish Khanna, Law Kumar Singh, Rekha Singh, Satish J. Sharma, Ashish Khanna, Deepak Gupta and G. Yamuna and has published in prestigious journals such as Computers in Biology and Medicine, Multimedia Tools and Applications and Advances in Engineering Software.

In The Last Decade

Shankar Thawkar

23 papers receiving 487 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shankar Thawkar India 14 228 218 142 78 53 23 511
Rekha Singh India 14 170 0.7× 182 0.8× 116 0.8× 83 1.1× 47 0.9× 20 418
Noppadol Maneerat Thailand 14 84 0.4× 260 1.2× 198 1.4× 164 2.1× 81 1.5× 41 506
Md. Omaer Faruq Goni Bangladesh 13 182 0.8× 312 1.4× 173 1.2× 89 1.1× 70 1.3× 19 589
Grace Ugochi Nneji China 14 236 1.0× 263 1.2× 118 0.8× 40 0.5× 42 0.8× 45 477
Sonali Dash India 15 106 0.5× 139 0.6× 206 1.5× 68 0.9× 82 1.5× 37 446
Eswaran Perumal India 11 235 1.0× 215 1.0× 95 0.7× 28 0.4× 37 0.7× 36 525
Abeer Saber Egypt 13 408 1.8× 222 1.0× 156 1.1× 6 0.1× 142 2.7× 24 694
Murat Canayaz Türkiye 8 167 0.7× 159 0.7× 65 0.5× 28 0.4× 26 0.5× 25 337
Parthasarathi Mangipudi India 11 62 0.3× 292 1.3× 249 1.8× 235 3.0× 71 1.3× 27 521
Wei-Bang Chen United States 10 91 0.4× 121 0.6× 224 1.6× 78 1.0× 8 0.2× 54 462

Countries citing papers authored by Shankar Thawkar

Since Specialization
Citations

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

Fields of papers citing papers by Shankar Thawkar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shankar Thawkar

This figure shows the co-authorship network connecting the top 25 collaborators of Shankar Thawkar. A scholar is included among the top collaborators of Shankar Thawkar 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 Shankar Thawkar. Shankar Thawkar 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.
Singh, Law Kumar, et al.. (2024). Correction to: Features fusion based novel approach for efficient blood vessel segmentation from fundus images. Multimedia Tools and Applications. 83(28). 72175–72175. 2 indexed citations
2.
Khanna, Munish, et al.. (2023). PlaNet: a robust deep convolutional neural network model for plant leaves disease recognition. Multimedia Tools and Applications. 83(2). 4465–4517. 48 indexed citations
3.
Khanna, Munish, et al.. (2023). Deep learning based computer-aided automatic prediction and grading system for diabetic retinopathy. Multimedia Tools and Applications. 82(25). 39255–39302. 38 indexed citations
4.
Singh, Law Kumar, Munish Khanna, Shankar Thawkar, & Rekha Singh. (2023). Nature-inspired computing and machine learning based classification approach for glaucoma in retinal fundus images. Multimedia Tools and Applications. 82(27). 42851–42899. 29 indexed citations
5.
Thawkar, Shankar, et al.. (2023). Breast cancer: A hybrid method for feature selection and classification in digital mammography. International Journal of Imaging Systems and Technology. 33(5). 1696–1712. 15 indexed citations
6.
Singh, Law Kumar, Munish Khanna, Shankar Thawkar, & Rekha Singh. (2023). Deep-learning based system for effective and automatic blood vessel segmentation from Retinal fundus images. Multimedia Tools and Applications. 83(2). 6005–6049. 33 indexed citations
7.
Thawkar, Shankar. (2022). Feature selection and classification in mammography using hybrid crow search algorithm with Harris hawks optimization. Journal of Applied Biomedicine. 42(4). 1094–1111. 13 indexed citations
8.
9.
Singh, Law Kumar, Munish Khanna, Shankar Thawkar, & Rekha Singh. (2022). Collaboration of features optimization techniques for the effective diagnosis of glaucoma in retinal fundus images. Advances in Engineering Software. 173. 103283–103283. 28 indexed citations
10.
Thawkar, Shankar, Satish J. Sharma, Munish Khanna, & Law Kumar Singh. (2021). Breast cancer prediction using a hybrid method based on Butterfly Optimization Algorithm and Ant Lion Optimizer. Computers in Biology and Medicine. 139. 104968–104968. 89 indexed citations
11.
Khanna, Munish, et al.. (2021). Radiologist-Level Two Novel and Robust Automated Computer-Aided Prediction Models for Early Detection of COVID-19 Infection from Chest X-ray Images. Arabian Journal for Science and Engineering. 48(8). 11051–11083. 32 indexed citations
12.
Thawkar, Shankar, Law Kumar Singh, & Munish Khanna. (2021). Multi-objective techniques for feature selection and classification in digital mammography. Intelligent Decision Technologies. 15(1). 115–125. 5 indexed citations
13.
Singh, Law Kumar, et al.. (2021). Robustness for Authentication of the Human Using Face, Ear, and Gait Multimodal Biometric System. International Journal of Information System Modeling and Design. 12(1). 39–72. 4 indexed citations
14.
Thawkar, Shankar, et al.. (2018). Classification of Masses in Digital Mammograms Using Firefly based Optimization. International Journal of Image Graphics and Signal Processing. 10(2). 25–33. 14 indexed citations
15.
Thawkar, Shankar, et al.. (2018). Classification of Masses in Digital Mammograms Using the Genetic Ensemble Method. Journal of Intelligent Systems. 29(1). 831–845. 7 indexed citations
16.
Thawkar, Shankar, et al.. (2018). Classification of masses in digital mammograms using Biogeography-based optimization technique. Journal of King Saud University - Computer and Information Sciences. 32(10). 1140–1148. 27 indexed citations
17.
Thawkar, Shankar, et al.. (2017). EFFICIENT APPROACH FOR THE CLASSIFICATION OF MASSES IN DIGITAL MAMMOGRAMS. International journal of innovative computing, information & control. 13(3). 978. 3 indexed citations
18.
Thawkar, Shankar, et al.. (2016). Automatic Detection and Classification of Masses in Digital Mammograms. International journal of intelligent engineering and systems. 10(1). 65–74. 22 indexed citations
19.
Thawkar, Shankar, et al.. (2015). Automatic Detection and Classification of Masses in Digital Mammograms. 2(1). 29–42. 7 indexed citations
20.
Yamuna, G., et al.. (2011). Protection of Digital Image Based on Wavelet Transform. 3(13). 864–867. 1 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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