CSE - ARTIFICIAL INTELLIGENCE & MACHINE LEARNING

Ms. T. Bhargavi

Ms. T. Bhargavi

Assistant Professor (CSE-AI & ML)
bhargavi.t@bvrithyderabad.edu.in

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Ph.D.: Plant Stress detection and Classification using Deep Learning Methodologies – Thesis Submitted
M.Tech.: JNTUK, 2018
B.Tech : JNTUK, 2016

Teaching Experience: 2 Years
Research Experience: Nil
Industry Experience:  Nil

Scopus ID: 58153470400
WoS ID: KIK-1013-2024
Google Scholar ID: YlyhRcoAAAAJ
Vidwan ID: 632715
ORCID ID: 0000-0002-7451-4085

Deep Learning, Image Processing.

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  1. 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
  2. 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
  1. 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)
  2. J. 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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