Road detection and segmentation by aerial images using CNN based system
Kurapati.Priyanka, Dr. Patnala S.R Chandra Murthy
Machine learning, Classifier, random forest
In This paper, proposes a system architecture based on deep convolutional neural network (CNN) for road detection and segmentation from aerial images.images are acquired by an unmanned aerial vehicle implemented by the authors. The algorithm for image segmentation has two phases.one is learning phase and another one is operating phase.the input images are decomposed and preprocessed in matlab and partitioned in dimension of 33x33 pixels using a sliding box algorithm these are considered as input into deep CNN.and CNN was design by MatConvNet and some structures.those are four convolutional layers, four pooling layers, one ReLu layer, one full connected layer, and a Softmax layer. The CNN was implemented using programming in MATLAB on GPU and the results are promising.