Identification and Grading of Freehand Sketches Using Deep Learning Techniques

A great deal of work has been done in the zone of computer vision on images. Be that as it may, the region of freehand sketches stays to be an unexplored zone. Freehand sketches fluctuate in light of masterful style. In spite of the fact that they contain minimum details, people can predict the class to which the sketch has a place. Concentrating on such negligibly itemized sketches can help us in understanding the neurobiological procedures that occur in people. In this paper, a Convolutional Neural Network (CNN) has been developed which can classify the freehand sketches in view of specific highlights. Classified freehand sketches are graded relative to the prototype being considered. Publicly available dataset of Eitz et al. is considered for identification and grading. Evaluating the sketches will help in surveying the advance of a client who is figuring out how to draw outlines.