A disaster classification application using convolutional neural network by performing data augmentation

Mummaneni Sobhana, Smitha Chowdary Chaparala, Devaganugula N. V. S. L. S. Indira, Konduru Kranthi Kumar


Natural disasters are catastrophic events and cause havoc to human life. These events occur in the most unpredictable times and are beyond human control. The aftermath of the disasters is devastating ranging from loss of life to relocation of large groups of the population. With the development in the domains of computer vision (CV) and Image processing, machine learning and deep learning models can integrate images and perform predictions. Deep learning techniques employ many robust techniques and provide significant results even in the case of images. The detection of natural disasters without human intervention requires the help of deep learning techniques. The project aims to employ a multi-layered convolutional neural network (CNN) organization to classify the images related to natural disasters related to earthquakes, floods, cyclones, and wildfires.


Computer vision; Convolutional neural networks; Deep learning; Image processing; Natural disasters

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DOI: http://doi.org/10.11591/ijeecs.v27.i3.pp1712-1720


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