Sesión especial sobre Deep Learning @ IWINAC 2017 (A Coruña)

IWINAC (http://www.iwinac.uned.es/iwinac2017/).

+ Special session +++++++++++++++++++++++++++++++++++++++++++

Chairperson: Alfredo Cuesta Infante
Co-chairperson: Juan Jose Pantrigo

Deep Learning has meant a breakthrough in the artificial intelligence community. The best performances attained so far in many fields, such as Computer Vision or Natural Language Processing, have been overtaken by these novel paradigm up to a point that only ten years ago was just science fiction. In addition, this technology has been open sourced by the main IA companies; and hence making quite straightforward to design, train and integrate deep-learning based systems. We open this session to both theoretical and practical works on deep learning.

Main topics include (but not restricted to):

– Deep architechtures
– Bayesian approaches to Deep Learning
– 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
– …

+ 6 special Issues associated +++++++++++++++++++++++++++++++++++++++++++

IWINAC is a great opportunity for presenting “work in progress” papers because there is a chance of extending the work if it is selected for one out of the six special issues in high impact journals (http://www.iwinac.uned.es/iwinac2017/journals/journals.html)

+ How to submit +++++++++++++++++++++++++++++++++++++++++++++

Proposals have to be sent by email both to alfredo.cuesta@urjc.es and juanjose.pantrigo@urjc.es.
If it fits in the scope of the session there will be a  clearance for uploading to the system.
Manuscripts must be in LNCS format, with a maximum of ten pages including references, figures and tables.
Please, see more info at IWINAC website.