Deep learning for image classification
Ryan McCoppin, Mateen M. Rizki · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2014
This paper provides an overview of deep learning and introduces the several subfields of deep learning including a specific tutorial of convolutional neural networks. Traditional methods for learning image features are compared to deep learning techniques. In addition, we present our preliminary classification results, our basic implementation of a convolutional restricted Boltzmann machine on the Mixed National Institute of Standards and Technology database (MNIST), and we explain how to use deep learning networks to assist in our development of a robust gender classification system.