This paper outlines a study on the effectiveness of deep learning techniques at detecting voids given photographs of concrete surfaces. The proposed deep learning model makes use of a convolutional neural network (CNN) and an artificial neural network (ANN). The model was trained on a dataset of 4,032 images of sizes 32x32 and 128x128, and subsequently obtained a training accuracy of 92.08% and a validation accuracy of 89.08%.
J.N. Mwero, C.K. Lagat (2019); Detection of Voids on Concrete Surface Using Deep Learning Model; International Journal of Scientific and Research Publications (IJSRP)
9(6) (ISSN: 2250-3153), DOI: http://dx.doi.org/10.29322/IJSRP.9.06.2019.p9060