Vinay Gautam

1.5k total citations · 1 hit paper
90 papers, 881 citations indexed

About

Vinay Gautam is a scholar working on Plant Science, Artificial Intelligence and Analytical Chemistry. According to data from OpenAlex, Vinay Gautam has authored 90 papers receiving a total of 881 indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Plant Science, 15 papers in Artificial Intelligence and 15 papers in Analytical Chemistry. Recurrent topics in Vinay Gautam's work include Smart Agriculture and AI (36 papers), Spectroscopy and Chemometric Analyses (15 papers) and Leaf Properties and Growth Measurement (12 papers). Vinay Gautam is often cited by papers focused on Smart Agriculture and AI (36 papers), Spectroscopy and Chemometric Analyses (15 papers) and Leaf Properties and Growth Measurement (12 papers). Vinay Gautam collaborates with scholars based in India, Indonesia and Saudi Arabia. Vinay Gautam's co-authors include Naresh Kumar Trivedi, Prabhjot Kaur, Shilpi Harnal, Abhineet Anand, Nitin Goyal, Mukund Pratap Singh, Santar Pal Singh, Divya Anand, Seifedine Kadry and Hani Moaiteq Aljahdali and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and Sensors.

In The Last Decade

Vinay Gautam

69 papers receiving 829 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.

Early Detection and Classification of Tomato Leaf Disease Using High-Performance Deep Neural Network

2021 235 citations Naresh Kumar Trivedi, Vinay Gautam et al. Sensors profile →

Peers

Vinay Gautam

PS

AC

AI

ECOLO

CVPR

Emine Uçar Türkiye

Tariq Hussain China

Naresh Kumar Trivedi India

Edna C. Too Kenya

Kemal Adem Türkiye

Shilpi Harnal India

Jiang Lu China

Mürvet Kırcı Türkiye

Amit Prakash Singh India

Geeta Rani India

Emine Uçar Türkiye

Vinay Gautam

482 ×0.8

PS

187 ×0.9

AC

95 ×1.0

AI

75 ×0.8

ECOLO

59 ×0.8

CVPR

Citations per year, relative to Vinay Gautam Vinay Gautam (= 1×) peers Emine Uçar

Countries citing papers authored by Vinay Gautam

Since Specialization

Citations

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

Fields of papers citing papers by Vinay Gautam

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Vinay Gautam

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Gautam, Vinay, et al.. (2025). Composite deep learning model for characterization of tomato leaf disease. Multimedia Tools and Applications. 84(38). 47021–47050.

2.

Gautam, Vinay, et al.. (2025). A lightweight deep learning method for medicinal leaf image classification using feature fusion. Scientific Reports. 15(1). 34417–34417.

3.

Tiwari, Raj Gaurang, et al.. (2024). Adaptive neuro-FUZZY inference system-fusion-deep belief network for brain tumor detection using MRI images with feature extraction. Biomedical Signal Processing and Control. 103. 107387–107387. 1 indexed citations

4.

Trivedi, Naresh Kumar, et al.. (2024). Deep Acne: Advancing Automated Acne Identification through Deep Neural Networks. 1–5. 2 indexed citations

5.

Tiwari, Raj Gaurang, et al.. (2023). Transfer Learning-Based Optimized Deep Learning Model to Characterize Mango Leaf Disease. 1217–1223. 2 indexed citations

6.

Gautam, Vinay, Raj Gaurang Tiwari, & Naresh Kumar Trivedi. (2023). Heritage Tourism and Religious Identity: A Deep Neural Network-Based Deductive Classification Approach. 15. 404–408. 7 indexed citations

7.

Trivedi, Naresh Kumar, et al.. (2023). Enhancing Military Surveillance: Advanced Aircraft Image Identification using Hybrid Deep Neural Networks. 5. 1545–1550.

8.

Trivedi, Naresh Kumar, et al.. (2023). Alzheimer’s Disease Detection and Classification: An Ensemble Machine Learning Paradigm. 76. 1–5. 1 indexed citations

9.

Gautam, Vinay, et al.. (2023). Enhancing Face Forgery Detection in a Decentralized Landscape: A Federated Learning Approach with ResNet. 1295–1301.

10.

Gautam, Vinay, Raj Gaurang Tiwari, Naresh Kumar Trivedi, Anuj Kumar Jain, & Vikrant Sharma. (2023). Artificial Intelligence Based Approach to Identify Plastic Bottle for Environment Sustainability. 1–4. 1 indexed citations

11.

Gautam, Vinay, et al.. (2023). Transfer learning based optimized deep neural network for pistachio classification. AIP conference proceedings. 2931. 60010–60010.

12.

Tiwari, Raj Gaurang, et al.. (2023). Enhancing Toxoplasmosis Chorioretinitis Detection: A Hybrid ResNet-YOLO Classifier with Fitness Sorted-Shark Smell Optimization. 77–82. 1 indexed citations

13.

Gautam, Vinay, Raj Gaurang Tiwari, Naresh Kumar Trivedi, & Anuj Kumar Jain. (2023). Multiclass X-Ray Image Classification Using Transfer Learning Based Deep Neural Network. 291–296. 1 indexed citations

14.

Trivedi, Naresh Kumar, Sunil Shukla, Raj Gaurang Tiwari, Ambuj Kumar Agarwal, & Vinay Gautam. (2023). Liver Cancer Diagnosis with Lightweight Federated Learning Using Identically Distributed Images. 25. 562–566. 1 indexed citations

15.

Anand, Abhineet, et al.. (2022). Cybersecurity Solutions Using AI Techniques. 2022 10th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO). 1–8. 2 indexed citations

16.

Gautam, Vinay, Naresh Kumar Trivedi, Aman Singh, et al.. (2022). A Transfer Learning-Based Artificial Intelligence Model for Leaf Disease Assessment. Sustainability. 14(20). 13610–13610. 45 indexed citations

17.

Trivedi, Naresh Kumar, et al.. (2022). Identification of Rice Varieties Using Machine Learning Algorithms. 10. 266–271. 10 indexed citations

18.

Simaiya, Sarita, et al.. (2021). EEPSA: Energy Efficiency Priority Scheduling Algorithm for Cloud Computing. 2021 2nd International Conference on Smart Electronics and Communication (ICOSEC). 1064–1069. 7 indexed citations

19.

Trivedi, Naresh Kumar, Vinay Gautam, Abhineet Anand, et al.. (2021). Early Detection and Classification of Tomato Leaf Disease Using High-Performance Deep Neural Network. Sensors. 21(23). 7987–7987. 235 indexed citations breakdown →

20.

Kumar, Anil, et al.. (2014). SOCIAL NETWORKING IN SMARTPHONE THROUGH A PROTOTYPE IMPLEMENTATION USING ANDROID. Journal of Global Research in Computer Sciences. 5(3). 8–13.

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.

Explore authors with similar magnitude of impact