Deep Learning Applications
(Co-located with the Seventh International Conference on Innovative 
Computing Technology (INTECH 2017)
Luton, UK &
Porto, Portugal
August 16-18, 2017
(www.dirf.org/intech)
(www.dirf.org/intechporto)

Deep Learning (DL) is an important component of computational 
intelligence which has the core domain machine learning research in it. 
It provides more efficient algorithms to deal with large-scale data in 
neuroscience, computer vision, speech recognition, language processing, 
biomedical informatics, recommender systems, learning theory, robotics, 
games, and so on. DL is gaining applications in many domains due to the 
availability of large amount of data coupled with machine learning 
algorithms.  As the DL applications are on increasing trend a workshop 
on it will enable to identify the emerging trends in the domain.

The proposed workshop will address the below listed but not limited 
themes.

Neural network architectures
DL Applications to the Natural Sciences
Visual Perception using Deep Convolutional Neural Networks
Deep Learning for Computer Vision
Deep Sequence Modeling: Historical Perspective and Current Trends
Automatic Terminology Extraction
Deep Learning of Behaviors
Probabilistic Graphical Models Algorithms
Deep Learning for Natural Language Processing
Deep Learning Applications at the Enterprise Scale
Multi-modal Deep Learning
Deep Learning Security
Neural Networks
 From Statistical Decision Theory and Deep Neural Networks
Machine Learning and Deep Neural Networks
Cognitive Architectures for Object Recognition in Video
Learning Representations for Vision, Speech and Text Processing 
Applications
Deep Learning in the Brain
Deep Learning for Sequences
Interpretable Deep Learning Models for Healthcare Applications
Deep Learning for Video Games
Data Processing Methods, and Applications of Least Squares Support 
Vector Machines
Deep Generative Models and Unsupervised Learning
Natural Language Understanding

Submissions

Submissions should provide original and unpublished research results or 
ongoing research with simulations. The papers should be between 6 to 8 
pages total in length in the IEEE format.

* All the accepted papers will appear in the proceedings published by 
IEEE and fully indexed by IEEE Xplore.

* Modified version of the selected papers will appear in the special 
issues of many peer reviewed and indexed journals.

Important Dates

Submission of papers: June 01, 2017
Notification of Acceptance/Rejection: July 01, 2017
Camera Ready: August 01, 2017
Registration August 01, 2017
Conference: August 16-18, 2017

Organizers

Ricardo Rodriguez Jorge, Engineering and Technology Institute, Mexico

Submissions at-http://www.dirf.org/intech/paper-submission/

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