Ms. T. Bhargavi
Assistant Professor (CSE-AI & ML)
bhargavi.t@bvrithyderabad.edu.in
AICTE ID: –
JNTUH ID: –
Ratified Status: –
Ph.D.: Plant Stress detection and Classification using Deep Learning Methadologies- Thesis Submitted
M.Tech.: JNTUK, 2018
B.Tech : JNTUK, 2016
Teaching Experience: 2 Years
Research Experience: Nil
Industry Experience: Nil
Scopus ID: https://www.scopus.com/authid/detail.uri?authorId=58153470400
WoS ID: KIK-1013-2024
Google Scholar ID: https://scholar.google.com/citations?user=YlyhRcoAAAAJ&hl=en
Vidwan ID: https://vidwan.inflibnet.ac.in/profile/632715/NjMyNzE1
ORCID ID: 0000-0002-7451-4085
Deep Learning, Image Processing.
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- Detection and Classification of Plant Stress Using Hybrid Deep Convolution Neural Networks: A Multi-Scale Vision Transformer Approach.https://doi.org/10.18280/ts.400625
- Bhargavi, T., and D. Sumathi. “Early detection of abiotic stress in plants through SNARE proteins using hybrid feature fusion model.” PeerJ Computer Science 10 (2024): e2149. 10.7717/peerj-cs.2149
- Bhargavi, T., and D. Sumathi. “Significance of Data Augmentation in Identifying Plant Diseases using Deep Learning.” 2023 5th International Conference on Smart Systems and Inventive Technology(ICSSIT)..https://ieeexplore.ieee.org/abstract/document/10061007.(SCOPUS)
- Bhaskar, V. N. Kumar, L. V. Naidu, R. D. Reddy, T. Bhargavi and S. D, “Paddy Leaf Disease Detection,” 2024 10th International Conference on Advanced Computing and Communication Systems (ICACCS), Coimbatore, India, 2024, pp. 2031-2036, doi: 10.1109/ICACCS60874.2024.10717015. (SCOPUS)
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