Ariz Abbas Naqvi
Department of Liberal Arts, Aligarh Muslim University, Aligarh, India
Download PDF http://doi.org/10.37648/ijrst.v11i04.002
In Computer Vision and image classification task, convolutional neural networks (CNNs) have demonstrated high performance. Their use in fire detection systems will make detection much more accurate, reducing the number of fire disasters and their ecological and social effects. However, implementation in real-world surveillance networks of CNN-based fire detection systems poses the greatest risk due to their high inference memory and computational requirements. An original, energy-efficient, and computationally efficient design is presented in this paper.
Keywords: convolutional neural networks, fire detection; Computer Vision Image Processing Technique
Disclaimer: Indexing of published papers is subject to the evaluation and acceptance criteria of the respective indexing agencies. While we strive to maintain high academic and editorial standards, International Journal of Research in Science and Technology does not guarantee the indexing of any published paper. Acceptance and inclusion in indexing databases are determined by the quality, originality, and relevance of the paper, and are at the sole discretion of the indexing bodies.