APPLICATION OF CONVOLUTIONAL NEURAL NETWORK TO AERIALPHOTOS FOR TSUNAMI DEBRIS DETECTION

DOI Web Site 1 Citations 3 References Open Access

Bibliographic Information

Other Title
  • 航空写真からの津波瓦礫判別におけるCNNの適用

Abstract

<p> In this study, Convolutional Neural Network (CNN) was applied to aerial photographs after the 2011 tsunami for detection of tsunami debris. Five different sample areas were chosen respectively from Miyagi and Iwate prefectures. The sample images were divided into small square images, and the divided images were classified into 5 classes (debris, vegetation, road, building and others) by visual identification as the training data for the network. The trained networks were able to differenciate the 4 main classes (debris, vegetation, road and building) with higher accuracy, while the class “others” had more misidentifications to reduce the total accuracy. Although there are some problems to be improved in the current method for the classification, it was found that CNN is effective in tsunami debris detection from the ortho images.</p>

Journal

Citations (1)*help

See more

References(3)*help

See more

Related Projects

See more

Keywords

Details 詳細情報について

Report a problem

Back to top