Automated Identification of Hookahs (Waterpipes) on Instagram: An Application in Feature Extraction Using Convolutional Neural Network and Support Vector Machine Classification.

Journal: Journal of medical Internet research
Published Date:

Abstract

BACKGROUND: Instagram, with millions of posts per day, can be used to inform public health surveillance targets and policies. However, current research relying on image-based data often relies on hand coding of images, which is time-consuming and costly, ultimately limiting the scope of the study. Current best practices in automated image classification (eg, support vector machine (SVM), backpropagation neural network, and artificial neural network) are limited in their capacity to accurately distinguish between objects within images.

Authors

  • Youshan Zhang
    Department of Computer Science, Lehigh University, Bethlehem, PA, United States.
  • Jon-Patrick Allem
    Keck School of Medicine, University of Southern California, Los Angeles, CA, United States.
  • Jennifer Beth Unger
    Keck School of Medicine of USC, Los Angeles, CA, United States.
  • Tess Boley Cruz
    Keck School of Medicine of USC, Los Angeles, CA, United States.