• Himanshu Sharma
• Prashant Powar
• V.G. Sridhar

Early detection of cracks in building walls it is quite important as these are early indicators for the ageing, decaying or any internal structural fault. This project aims to develop an automatic inspection system based on deep learning model and image processing to identify cracks. Transfer learning models of convolutional neural networks (CNNs) are used to learn the intrinsic features of cracks using the images of the surfaces, which help them for the automatic classification into cracked/un-cracked classes

CNN, Deep learning

"CNN BASED WALL CRACK DETECTION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 10, page no.a286-a289, October-2021, Available :http://www.jetir.org/papers/JETIR2110038.pdf

"CNN BASED WALL CRACK DETECTION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 10, page no. ppa286-a289, October-2021, Available at : http://www.jetir.org/papers/JETIR2110038.pdf