Transfer Learning and Custom Built VGG and CNN-SVM Models for Wildfire Detection IEEE Conference

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Title: Comprehensive and Comparative Analysis between Transfer Learning and Custom Built VGG and CNN-SVM Models for Wildfire Detection

In Proceeding of the 2024 IEEE International Conference On Intelligent Computing in Data Sciences (ICDS’24), Marrakech, Morocco

Authors: Aditya V. Jonnalagadda, Hashim A Hashim, and Andrew Harris

Authors are with the Department of Mechanical and Aerospace Engineering at Carleton University, Ottawa, Ontario, Canada

The conference was presented by Aditya V. Jonnalagadda

This work was supported in part by the National Sciences and Engineering
Research Council of Canada (NSERC) under the grants RGPIN-2022-04937.

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[Ref1] A. V. Jonnalagadda, H. A. Hashim, and A. Harris, “Comprehensive and Comparative Analysis between Transfer Learning and Custom Built VGG and CNN-SVM Models for Wildfire Detection,” In Proc. of the 2024 IEEE International Conference On Intelligent Computing in Data Sciences (ICDS’24), Marrakech, Morocco, pp. 1-7, 2024.
URL: http://dx.doi.org/10.1109/ICDS62089.2...
PDF arXiv: https://arxiv.org/pdf/2411.08171.pdf

Other readings:
[Ref2] A. V. Jonnalagadda and H. A. Hashim, “SegNet: A Segmented Deep Learning based Convolutional Neural Network Approach for Drones Wildfire Detection,” Remote Sensing Applications: Society and Environment (RSA-SE), Vol. 34, pp. 101181, 2024.
URL: https://doi.org/10.1016/j.rsase.2024....
PDF arXiv: https://arxiv.org/pdf/2405.00031.pdf
Video Experiment    • Drone Wildfire Detection Deep Learning Alg...  
Discussion:    • SegNet Segmented Deep Learning Convolution...