Publication Type:

Journal Article

Source:

CoRR, Volume abs/1805.04424 (2018)

URL:

http://arxiv.org/abs/1805.04424

Abstract:

Convolutional neural networks are the most widely used deep learning algorithms for traffic signal classification till date but they fail to capture pose, view, orientation of the images because of the intrinsic inability of max pooling layer. This paper proposes a novel method for Traffic sign detection using deep learning architecture called capsule networks that achieves outstanding performance on the German traffic sign dataset. Capsule network consists of capsules which are a group of neurons representing the instantiating parameters

Cite this Research Publication

A. Dinesh Kumar and Karthika, R., “Novel Deep Learning Model for Traffic Sign Detection Using Capsule Networks”, CoRR, vol. abs/1805.04424, 2018.