Deep learning for image classification

Ryan McCoppin; Mateen Rizki

doi:10.1117/12.2054045

10 June 2014 Deep learning for image classification

Ryan McCoppin, Mateen Rizki

Proceedings Volume 9079, Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR V; 90790T (2014) https://doi.org/10.1117/12.2054045
Event: SPIE Defense + Security, 2014, Baltimore, MD, United States

Abstract

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.

Citation Download Citation

Ryan McCoppin and Mateen Rizki "Deep learning for image classification", Proc. SPIE 9079, Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR V, 90790T (10 June 2014); https://doi.org/10.1117/12.2054045

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