A hybrid deep learning model by combining convolutional neural network and recurrent neural network to detect forest fire

• Published in: Multimedia tools and applications Vol. 81; no. 27; pp. 38643 - 38660
• Main Authors: Ghosh, Rajib, Kumar, Anupam
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.11.2022; Springer Nature B.V
• Subjects: Artificial neural networks; Classification; Computer Communication Networks; Computer Science; Computer vision; Data Structures and Information Theory; Datasets; Deep learning; Feature extraction; Feature maps; Forest fire detection; Machine learning; Multimedia Information Systems; Neural networks; Recurrent neural networks; Special Purpose and Application-Based Systems; Vision systems; Deep learning; Forest fire; Recurrent neural network; Convolutional neural network

Forest fire poses a serious threat to wildlife, environment, and all mankind. This threat has prompted the development of various intelligent and computer vision based systems to detect forest fire. This article proposes a novel hybrid deep learning model to detect forest fire. This model uses a com...