Convolution Optimization in Fire Classification
Author:
Affiliation:
1. Escola Politécnica de Pernambuco, Universidade de Pernambuco, Recife, Brazil
2. School of Information Technology, Deakin University, Geelong, VI, Australia
3. Centro de Informática, Universidade Federal de Pernambuco, Recife, Brazil
Funder
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior—Brazil (CAPES)—Finance Code 001
Fundação de Amparo a Ciência e Tecnologia do Estado de Pernambuco
Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)—Brazilian Research Agencies
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Engineering,General Materials Science,General Computer Science
Link
http://xplorestaging.ieee.org/ielx7/6287639/9668973/09714344.pdf?arnumber=9714344
Reference50 articles.
1. Deep Convolutional Neural Network for Fire Detection
2. Lightweight and efficient octave convolutional neural network for fire recognition
3. An intelligent fire detection approach through cameras based on computer vision methods
4. Real time video fire detection using spatio-temporal consistency energy
5. Spatio-Temporal Flame Modeling and Dynamic Texture Analysis for Automatic Video-Based Fire Detection
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