Malladi, L. A., & Gupta, N., & El-Sayed, A., & Xiong, X. (2025, March), Revolutionizing Wildfire Detection with Convolutional Neural Networks: A VGG16 Model Approach  Paper presented at 2025 Northeast Section Conference, University of Bridgeport, Bridgeport, CT. 10.18260/1-2-119.1115-54974

\bibitem{asee_peer_54974}
  Malladi, L. A., \& Gupta, N., \& El-Sayed, A., \& Xiong, X. (2025, March), \emph{Revolutionizing Wildfire Detection with Convolutional Neural Networks: A VGG16 Model Approach}
  Paper presented at 2025 Northeast Section Conference, University of Bridgeport, Bridgeport, CT.
  10.18260/1-2-119.1115-54974

Lakshmi Aishwarya Malladi, Navarun Gupta, Ahmed El-Sayed, and Xingguo Xiong.  "Revolutionizing Wildfire Detection with Convolutional Neural Networks: A VGG16 Model Approach".  2025 Northeast Section Conference, University of Bridgeport, Bridgeport, CT, 2025, March.  ASEE Conferences, 2025.  https://peer.asee.org/54974 Internet.  12 Jul, 2025

\bibitem{asee_peer_54974}
  Lakshmi Aishwarya Malladi, Navarun Gupta, Ahmed El-Sayed, and Xingguo Xiong.
  "Revolutionizing Wildfire Detection with Convolutional Neural Networks: A VGG16 Model Approach".
  \emph{2025 Northeast Section Conference, University of Bridgeport, Bridgeport, CT, 2025, March}.
  ASEE Conferences, 2025.
  https://peer.asee.org/54974 Internet.  12 Jul, 2025

@INPROCEEDINGS{asee_peer_54974
author = "Lakshmi Aishwarya Malladi, Navarun Gupta, Ahmed El-Sayed, and Xingguo Xiong"
title = "Revolutionizing Wildfire Detection with Convolutional Neural Networks: A VGG16 Model Approach"
booktitle = "2025 Northeast Section Conference"
year = "2025"
month = "March"
address = "University of Bridgeport, Bridgeport, CT"
publisher = "ASEE Conferences"
note = {https://peer.asee.org/54974}
number = {10.18260/1-2-119.1115-54974}
}

TY  - CPAPER
AU  - Lakshmi Aishwarya Malladi
AU  - Navarun Gupta
AU  - Ahmed El-Sayed
AU  - Xingguo Xiong
CY  - University of Bridgeport, Bridgeport, CT
DA  - 2025/03/23
PB  - ASEE Conferences
TI  - Revolutionizing Wildfire Detection with Convolutional Neural Networks: A VGG16 Model Approach
UR  - https://peer.asee.org/54974
DO  - 10.18260/1-2-119.1115-54974
ER  -