Sujata Chakravarty

901 total citations · 1 hit paper
52 papers, 497 citations indexed

About

Sujata Chakravarty is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computer Networks and Communications. According to data from OpenAlex, Sujata Chakravarty has authored 52 papers receiving a total of 497 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Artificial Intelligence, 13 papers in Computer Vision and Pattern Recognition and 10 papers in Computer Networks and Communications. Recurrent topics in Sujata Chakravarty's work include Network Security and Intrusion Detection (7 papers), Smart Agriculture and AI (7 papers) and Remote-Sensing Image Classification (7 papers). Sujata Chakravarty is often cited by papers focused on Network Security and Intrusion Detection (7 papers), Smart Agriculture and AI (7 papers) and Remote-Sensing Image Classification (7 papers). Sujata Chakravarty collaborates with scholars based in India, Egypt and Lebanon. Sujata Chakravarty's co-authors include Puspanjali Mohapatra, Satyabrata Dash, Debasish Das, P. Ravi Kiran Varma, Nimay Chandra Giri, Kareem M. AboRas, Amiya Kumar Rath, Georgios Fotis, Sachi Nandan Mohanty and N. Gowtham and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and Sensors.

In The Last Decade

Sujata Chakravarty

43 papers receiving 470 citations

Hit Papers

An optimized LSTM-based d... 2025 2026 2025 5 10 15 20
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.

  1. An optimized LSTM-based deep learning model for anomaly network intrusion detection
    2025 22 citations Sujata Chakravarty, Amiya Kumar Rath et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sujata Chakravarty India 12 168 88 78 73 58 52 497
Aybars Uğur Türkiye 14 247 1.5× 51 0.6× 102 1.3× 120 1.6× 75 1.3× 49 666
Radwa Marzouk Saudi Arabia 14 142 0.8× 28 0.3× 85 1.1× 131 1.8× 59 1.0× 58 478
Heba G. Mohamed Saudi Arabia 17 147 0.9× 56 0.6× 101 1.3× 165 2.3× 128 2.2× 73 695
Fawaz Waselallah Alsaade Saudi Arabia 14 245 1.5× 48 0.5× 108 1.4× 106 1.5× 59 1.0× 51 822
M. Thenmozhi India 8 124 0.7× 22 0.3× 113 1.4× 82 1.1× 43 0.7× 43 382
S. S. Bedi India 11 142 0.8× 35 0.4× 36 0.5× 224 3.1× 30 0.5× 41 578
Manel Ayadi Saudi Arabia 11 95 0.6× 42 0.5× 62 0.8× 81 1.1× 24 0.4× 34 354
Jaber S. Alzahrani Saudi Arabia 12 163 1.0× 23 0.3× 93 1.2× 91 1.2× 41 0.7× 67 481
L V Narasimha Prasad India 12 137 0.8× 220 2.5× 33 0.4× 85 1.2× 67 1.2× 54 665
Noha A. Hikal Egypt 11 146 0.9× 30 0.3× 175 2.2× 118 1.6× 84 1.4× 33 479

Countries citing papers authored by Sujata Chakravarty

Since Specialization
Citations

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

Fields of papers citing papers by Sujata Chakravarty

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sujata Chakravarty

This figure shows the co-authorship network connecting the top 25 collaborators of Sujata Chakravarty. A scholar is included among the top collaborators of Sujata Chakravarty 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 Sujata Chakravarty. Sujata Chakravarty 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.
Chakravarty, Sujata, et al.. (2025). Precision pest management in agriculture using Inception V3 and EfficientNet B4: A deep learning approach for crop protection. Information Processing in Agriculture. 13(1). 142–161.
2.
Das, Sudipta, et al.. (2025). Enhancing Traffic Monitoring Systems through Image Analysis and Rule-Based Machine Learning. Procedia Computer Science. 258. 2119–2129.
3.
Chakravarty, Sujata, et al.. (2025). An interactive AI-based crop and pest management system leveraging transfer learning for enhanced sustainable agriculture. Modeling Earth Systems and Environment. 11(4). 1 indexed citations
4.
Dash, Satyabrata, et al.. (2024). Performance Assessment of Different Sustainable Energy Systems Using Multiple-Criteria Decision-Making Model and Self-Organizing Maps. SHILAP Revista de lepidopterología. 12(3). 42–42. 19 indexed citations
5.
Chakravarty, Sujata, et al.. (2024). Deep learning model for elevating internet of things intrusion detection. International Journal of Power Electronics and Drive Systems/International Journal of Electrical and Computer Engineering. 14(5). 5874–5874. 3 indexed citations
6.
Dash, Satyabrata, Sujata Chakravarty, Nimay Chandra Giri, Ephraim Bonah Agyekum, & Kareem M. AboRas. (2024). Minimum Noise Fraction and Long Short-Term Memory Model for Hyperspectral Imaging. International Journal of Computational Intelligence Systems. 17(1). 7 indexed citations
7.
8.
Chakravarty, Sujata, et al.. (2024). Bioinformatics in Cancer: Key Proteins and Pathway Analysis. 858–863.
9.
Chakravarty, Sujata, et al.. (2023). An improved region-based embedding technique for data hiding and image recovery using multiple ROI and RONI. International Journal of Electronic Security and Digital Forensics. 15(2). 101–101. 2 indexed citations
10.
Gupta, Nidhi, Sujata Chakravarty, & Satyabrata Dash. (2023). Deep Learning Technique for Real-Time Forest Fire Detection from Video Streams. 19. 1–4.
11.
Chakravarty, Sujata, et al.. (2023). Automatic leaf diseases detection and classification of cucumber leaves using internet of things and machine learning models. International Journal of Web and Grid Services. 19(3). 350–388. 4 indexed citations
12.
Chakravarty, Sujata, et al.. (2023). Integration of Cellular IoT for Greenhouse Monitoring, Controlling and Notification System. 450–455. 1 indexed citations
13.
Varma, P. Ravi Kiran, et al.. (2023). Swarm Optimization and Machine Learning Applied to PE Malware Detection towards Cyber Threat Intelligence. Electronics. 12(2). 342–342. 16 indexed citations
14.
Chakravarty, Sujata, et al.. (2022). Smart Crop Recommender System-A Machine Learning Approach. 494–499. 24 indexed citations
15.
Chakravarty, Sujata, et al.. (2022). A Two-Tier Fuzzy Meta-Heuristic Hybrid Optimization for Dynamic Android Malware Detection. SN Computer Science. 4(2). 4 indexed citations
16.
Chakravarty, Sujata, et al.. (2022). Melanoma Detection from Skin Lesions using Convolution Neural Network. 1–5. 5 indexed citations
17.
Chakravarty, Sujata, et al.. (2021). Lung cancer detection using an integration of fuzzy K-Means clustering and deep learning techniques for CT lung images. Bulletin of the Polish Academy of Sciences Technical Sciences. 139006–139006. 4 indexed citations
18.
Dash, Satyabrata, et al.. (2021). A Deep Learning Method to Forecast COVID-19 Outbreak. New Generation Computing. 39(3-4). 515–539. 16 indexed citations
19.
Chakravarty, Sujata, et al.. (2020). Feature Selection and Evaluation of Permission-based Android Malware Detection. 795–799. 18 indexed citations
20.
Das, Debasish, et al.. (2020). Leaf Disease Detection using Support Vector Machine. 1036–1040. 63 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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