Shweta Lamba

699 total citations
29 papers, 426 citations indexed

About

Shweta Lamba is a scholar working on Plant Science, Analytical Chemistry and Artificial Intelligence. According to data from OpenAlex, Shweta Lamba has authored 29 papers receiving a total of 426 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Plant Science, 9 papers in Analytical Chemistry and 7 papers in Artificial Intelligence. Recurrent topics in Shweta Lamba's work include Smart Agriculture and AI (16 papers), Spectroscopy and Chemometric Analyses (9 papers) and COVID-19 diagnosis using AI (6 papers). Shweta Lamba is often cited by papers focused on Smart Agriculture and AI (16 papers), Spectroscopy and Chemometric Analyses (9 papers) and COVID-19 diagnosis using AI (6 papers). Shweta Lamba collaborates with scholars based in India, South Korea and Lebanon. Shweta Lamba's co-authors include Vinay Kukreja, Anupam Baliyan, Bhanu Sharma, Shalli Rani, Syed Hassan Ahmed, Avinash Sharma, Thippa Reddy Gadekallu, Jungeun Kim, Deepali Gupta and Junaid Rashid and has published in prestigious journals such as Frontiers in Plant Science, Sustainability and International Journal of Information Technology.

In The Last Decade

Shweta Lamba

26 papers receiving 414 citations

Peers

Shweta Lamba
Naresh Kumar Trivedi India
Hamoud Alshammari Saudi Arabia
G. Sambasivam India
Shilpi Harnal India
Mahmood A. Mahmood Saudi Arabia
Qin Zhi-guang China
Karim Gasmi Saudi Arabia
Md. Ashiqul Islam Bangladesh
R.S. Latha India
R. Cristin India
Naresh Kumar Trivedi India
Shweta Lamba
Citations per year, relative to Shweta Lamba Shweta Lamba (= 1×) peers Naresh Kumar Trivedi

Countries citing papers authored by Shweta Lamba

Since Specialization
Citations

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

Fields of papers citing papers by Shweta Lamba

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shweta Lamba

This figure shows the co-authorship network connecting the top 25 collaborators of Shweta Lamba. A scholar is included among the top collaborators of Shweta Lamba 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 Shweta Lamba. Shweta Lamba 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.
Lamba, Shweta, et al.. (2023). Multiple Grapes Leaf Disease Identification Using an Optimal Deep Learning Model: Xception. 1–6. 7 indexed citations
2.
Lamba, Shweta, et al.. (2023). Deep Learning-based Hybrid Model for Severity Prediction of Leaf Smut Sugarcane Infection. 1004–1009. 23 indexed citations
3.
Sharma, Bhanu, et al.. (2023). Alzheimer Detection Using Tuner Optimization with Deep Learning Algorithm. 12. 1–5. 1 indexed citations
4.
Lamba, Shweta, et al.. (2023). Pneumonia Classification Model using Deep Learning Algorithm. 249–253. 1 indexed citations
5.
Lamba, Shweta, et al.. (2023). An Improved Deep Learning Model for Forecasting Red Stripe Disease. 296–300. 1 indexed citations
6.
7.
Lamba, Shweta, et al.. (2023). Tea Leaf Diseases Classification and Detection using a Convolutional Neural Network. 498–502. 19 indexed citations
8.
9.
Lamba, Shweta, Vinay Kukreja, Junaid Rashid, et al.. (2023). A novel fine-tuned deep-learning-based multi-class classifier for severity of paddy leaf diseases. Frontiers in Plant Science. 14. 1234067–1234067. 11 indexed citations
10.
Lamba, Shweta, et al.. (2023). Pneumonia Classification using CNN-GAN. 456–461. 2 indexed citations
11.
Lamba, Shweta, et al.. (2023). Pneumonia Detection and Classification with CNN-GAN Augmentation Using Fine Tuning. 1–5. 1 indexed citations
12.
Baliyan, Anupam, et al.. (2023). A Novel Optimized Routing Protocol for Ad-hoc Network. 676–682.
13.
Lamba, Shweta, Vinay Kukreja, Anupam Baliyan, Shalli Rani, & Syed Hassan Ahmed. (2023). A Novel Hybrid Severity Prediction Model for Blast Paddy Disease Using Machine Learning. Sustainability. 15(2). 1502–1502. 72 indexed citations
14.
Lamba, Shweta, et al.. (2023). Deep Learning-based Approach for Leaf Disease of Sugarcane Classification. 176–180. 6 indexed citations
15.
Sharma, Bhanu, et al.. (2023). Alzheimer Detection Using CNN and GAN Augmentation. 1–5. 4 indexed citations
16.
Lamba, Shweta, Anupam Baliyan, & Vinay Kukreja. (2022). A novel GCL hybrid classification model for paddy diseases. International Journal of Information Technology. 15(2). 1127–1136. 74 indexed citations
17.
Lamba, Shweta, et al.. (2022). Optimized classification model for plant diseases using generative adversarial networks. Innovations in Systems and Software Engineering. 19(1). 103–115. 23 indexed citations
18.
Lamba, Shweta, Anupam Baliyan, & Vinay Kukreja. (2022). Generative Adversarial Networks based Data Augmentation for Paddy Disease Detection using Support Vector Machine. 2022 10th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO). 1–5. 10 indexed citations
19.
Lamba, Shweta, et al.. (2021). Role of Mathematics in Machine Learning. SSRN Electronic Journal. 4 indexed citations
20.
Lamba, Shweta, et al.. (2021). Advanced Encryption Standard: Attacks and Current Research Trends. 112–116. 19 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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