Sweta Jain

1.8k total citations · 1 hit paper
58 papers, 1.1k citations indexed

About

Sweta Jain is a scholar working on Computer Networks and Communications, Computer Vision and Pattern Recognition and Artificial Intelligence. According to data from OpenAlex, Sweta Jain has authored 58 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Computer Networks and Communications, 13 papers in Computer Vision and Pattern Recognition and 12 papers in Artificial Intelligence. Recurrent topics in Sweta Jain's work include Mobile Ad Hoc Networks (11 papers), Opportunistic and Delay-Tolerant Networks (9 papers) and COVID-19 diagnosis using AI (6 papers). Sweta Jain is often cited by papers focused on Mobile Ad Hoc Networks (11 papers), Opportunistic and Delay-Tolerant Networks (9 papers) and COVID-19 diagnosis using AI (6 papers). Sweta Jain collaborates with scholars based in India, Portugal and United States. Sweta Jain's co-authors include Mahesh Gour, T. Sunil Kumar, Jyoti Singhai, Meenu Chawla, Virendra Singh, M.K. Bhasin, Vijay Bhaskar Semwal, Vasco N. G. J. Soares, Joel J. P. C. Rodrigues and Sanyam Shukla and has published in prestigious journals such as Scientific Reports, Frontiers in Microbiology and Applied Soft Computing.

In The Last Decade

Sweta Jain

50 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.

Tomato plant disease detection using transfer learning with C-GAN synthetic images

2021 425 citations Sweta Jain, Mahesh Gour et al. profile →

Peers

Sweta Jain

PS

AI

RNMI

CNC

CVPR

Kemal Adem Türkiye

Ajay Kaul India

Prabira Kumar Sethy India

Santi Kumari Behera India

Siddharth Singh Chouhan India

Hasan Erbay Türkiye

Muhammed Fahri Ünlerşen Türkiye

Happy Nkanta Monday China

Serhat Kılıçarslan Türkiye

Ümit Atila Türkiye

Kemal Adem Türkiye

Sweta Jain

301 ×0.8

PS

250 ×0.8

AI

165 ×0.7

RNMI

28 ×0.1

CNC

159 ×1.0

CVPR

Citations per year, relative to Sweta Jain Sweta Jain (= 1×) peers Kemal Adem

Countries citing papers authored by Sweta Jain

Since Specialization

Citations

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

Fields of papers citing papers by Sweta Jain

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sweta Jain

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

All Works

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20 of 20 papers shown

1.

Semwal, Vijay Bhaskar, et al.. (2025). Explainable deep learning framework for lower limb activity classification using reconstructed sEMG signals in healthy and pathological subjects. Applied Soft Computing. 184. 113748–113748.

2.

Jain, Sweta, et al.. (2025). BioTransX: A novel bi-former based hybrid model with bi-level routing attention for brain tumor classification with explainable insights. Computers in Biology and Medicine. 195. 110515–110515.

3.

Semwal, Vijay Bhaskar, et al.. (2024). A smartphone-based human activities recognition using novel multi-stream movelets on fusion of accelerometer and gyroscope data and classification using different distance metrics. Multimedia Tools and Applications. 84(25). 30259–30280. 4 indexed citations

4.

Jain, Sweta, et al.. (2024). XAttentionHAR Ensemble: Leveraging Cross-Modal Attention for Enhanced Activity Recognition. International Journal of Pattern Recognition and Artificial Intelligence. 39(1).

5.

Jain, Sweta, et al.. (2024). Federated Learning for Privacy Preserving in Healthcare Data Analysis. 1–6.

6.

Gour, Mahesh, Sweta Jain, & T. Sunil Kumar. (2024). Robust nuclei segmentation with encoder‐decoder network from the histopathological images. International Journal of Imaging Systems and Technology. 34(4).

7.

Gour, Mahesh, et al.. (2024). Integrated ensemble CNN and explainable AI for COVID-19 diagnosis from CT scan and X-ray images. Scientific Reports. 14(1). 24985–24985. 14 indexed citations

8.

Jain, Sweta, et al.. (2024). EEG-Based Scalogram Imaging and Deep Learning for Insomnia Classification. 1–6. 1 indexed citations

9.

Gour, Mahesh, et al.. (2023). XCapsNet: A deep neural network for automated detection of diabetic retinopathy. International Journal of Imaging Systems and Technology. 33(3). 1014–1027. 9 indexed citations

10.

Jain, Sweta, et al.. (2023). Advanced IoT-Based Fire and Smoke Detection System leveraging Deep Learning and TinyML. 1–10. 2 indexed citations

11.

Gour, Mahesh & Sweta Jain. (2021). Uncertainty-aware convolutional neural network for COVID-19 X-ray images classification. Computers in Biology and Medicine. 140. 105047–105047. 52 indexed citations

12.

Gour, Mahesh & Sweta Jain. (2021). Automated COVID-19 detection from X-ray and CT images with stacked ensemble convolutional neural network. Journal of Applied Biomedicine. 42(1). 27–41. 49 indexed citations

13.

Jain, Sweta, et al.. (2021). Pulmonary Lung Nodule Detection from Computed Tomography Images Using Two-Stage Convolutional Neural Network. The Computer Journal. 66(4). 785–795. 12 indexed citations

14.

Jain, Sweta, et al.. (2021). HydroIoT: An IoT and Edge Computing based Multi-Level Hydroponics System. 1–6. 2 indexed citations

15.

Singh, Gurbir, et al.. (2019). Economics of Processing of Barley Grain into Malt in the Jaipur District of Rajasthan, India. International Journal of Current Microbiology and Applied Sciences. 8(10). 1541–1548. 1 indexed citations

16.

Singh, Jyotsna, Sweta Jain, Shaista Parveen, et al.. (2018). A novel mutation in SGSH causing Sanfillipo type 3A Mucopolysaccharidoses in an Indian family. Molecular Genetics and Metabolism Reports. 15. 124–126.

17.

Chauhan, Nar Singh, Rajesh Pandey, Shashank Gupta, et al.. (2018). Western Indian Rural Gut Microbial Diversity in Extreme Prakriti Endo-Phenotypes Reveals Signature Microbes. Frontiers in Microbiology. 9. 118–118. 33 indexed citations

18.

Jain, Sweta & Meenu Chawla. (2017). A fuzzy logic based buffer management scheme with traffic differentiation support for delay tolerant networks. Telecommunication Systems. 68(2). 319–335. 5 indexed citations

19.

Jain, Sweta, Meenu Chawla, & Nitin Gupta. (2013). Weighted Dynamic Bi-connected Group based Replica Allocation method for Mobile Ad Hoc Networks. 189–197. 2 indexed citations

20.

Bhasin, M.K. & Sweta Jain. (2007). Biology of the Tribal Groups of Rajasthan, India: 2. Physical Growth and Anthropometric Somatotypes. The Anthropologist. 9(3). 177–187. 2 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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