構造
ディープラーニングによるRC柱の損傷度判定に関する検討
2021 年 27 巻 66 号 p. 756-760
詳細
2021 年 27 巻 66 号 p. 756-760
It takes time to carry out the post-earthquake quick inspection of many damaged buildings after large earthquakes. As image classification method of damage level after earthquake, deep learning with convolutional neural network is applied to reinforced concrete columns. We achieve a classification accuracy of 77% by AlexNet and 80% by VGG16 in case of transfer learning. To show the reason of classification, Grad-cam is utilized.
