2:15 PM - 2:30 PM
[HTT19-09] Object detection of ground penetrating radar images using deep convolutional neural network and autoencoder
Keywords:Ground penetrating radar, Deep convolutional neural networks, Target detection
As a result of the application, the deep convolutional neural network showed the accuracy of 99.7-99.9 % in teaching data, while the accuracy was 93.9-99.7 % in validation data. On the other hand, the application of conventional neural networks with three layers showed the accuracy of 97.7-99.3 % in teaching data and 41.9-57.9 % in validation data, indicating significantly higher accuracy of the deep-convolutional neural network for validation data. The autoencoder optimized with typical patterns of objects with reverse polarity (higher relative permittivity) detected different image patterns that correspond to objects with lower relative permittivity. These results suggest the effectiveness of the deep learning algorithm to detect characteristic pattern in GPR images.