S10 - DEEP LEARNING

Chairs

Dr. Alfredo Cuesta, Universidad Rey Juan Carlos (Spain)

Dr. Juan J. Pantrigo, Universidad Rey Juan Carlos (Spain)

Dr. Antonio S. Montemayor, Universidad Rey Juan Carlos (Spain)

Abstract

Deep learning has meant a breakthrough in the artificial intelligence community, obtaining the best performance results in many fields, such as Computer Vision or Natural Language Processing. Moreover, the relevance of this paradigm have affected to a wide variety of fields, beyond computer science. We welcome both theoretical and practical works on deep learning.

Main topics include (but not restricted to):

  • Deep architechtures
  • Bayesian approaches to Deep Learning
  • Capsule networks
  • Generative models in Deep Learning
  • Restricted Boltzman Machines
  • Recurrent Neural Networks and Long-Short term memories
  • Feature representation
  • Spatial and Spatiotemporal clustering and classification
  • Human activity analysis
  • Biomedical data analysis
  • Signal processing
  • Natural language processing
  • Computer vision
  • Smart cities
  • ...