Multiple Flames Recognition Using Deep Learning

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Author(s): Chen Xin (Auckland University of Technology, New Zealand), Minh Nguyen (Auckland University of Technology, New Zealand)and Wei Qi Yan (Auckland University of Technology, New Zealand)
Copyright: 2020
Pages: 12
Source title: Handbook of Research on Multimedia Cyber Security
Source Author(s)/Editor(s): Brij B. Gupta (National Institute of Technology, Kurukshetra, India)and Deepak Gupta (LoginRadius Inc., Canada)
DOI: 10.4018/978-1-7998-2701-6.ch015

Keywords: Cyber and Network Security / Information Science Reference / Media & Communications / Multimedia Technology

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Abstract

Identifying fire flames is based on object recognition which has valuable applications in intelligent surveillance. This chapter focuses on flame recognition using deep learning and its evaluations. For achieving this goal, authors design a Multi-Flame Detection scheme (MFD) which utilises Convolutional Neural Networks (CNNs). Authors take use of TensorFlow in deep learning with an NVIDIA GPU to train an image dataset and constructed a model for flame recognition. The contributions of this book chapter are: (1) data augmentation for flame recognition, (2) model construction for deep learning, and (3) result evaluations for flame recognition using deep learning.

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Multiple Flames Recognition Using Deep Learning

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