Home      Log In      Contacts      FAQs      INSTICC Portal
 
DeLTA 2020 will be held in conjunction with DATA 2020, ICINCO 2020 and SIMULTECH 2020.
Registration to DeLTA allows free access to the DATA, ICINCO and SIMULTECH conferences (as a non-speaker).

 

Upcoming Deadlines

Regular Paper Submission: February 14, 2020
Regular Paper Authors Notification: April 15, 2020
Regular Paper Camera Ready and Registration: April 29, 2020

Deep Learning and Big Data Analytics are two major topics of data science, nowadays. Big Data has become important in practice, as many organizations have been collecting massive amounts of data that can contain useful information for business analysis and decisions, impacting existing and future technology. A key benefit of Deep Learning is the ability to process these data and extract high-level complex abstractions as data representations, making it a valuable tool for Big Data Analytics where raw data is largely unlabeled.

Machine-learning and artificial intelligence are pervasive in most real-world applications scenarios such as computer vision, information retrieval and summarization from structured and unstructured multimodal data sources, natural language understanding and translation, and many other application domains. Deep learning approaches, leveraging on big data, are outperforming state-of-the-art more “classical” supervised and unsupervised approaches, directly learning relevant features and data representations without requiring explicit domain knowledge or human feature engineering. These approaches are currently highly important in IoT applications.






Conference Chair

Kurosh MadaniUniversity of Paris-EST Créteil (UPEC), France

PROGRAM CHAIR

Ana FredInstituto de Telecomunicações and Instituto Superior Técnico - Lisbon University, Portugal






Doctoral Consortium

Submission: May 13, 2020
Submission: May 13, 2020
 
Publications:


All papers presented at the conference venue
will be available at the SCITEPRESS Digital Library
Ethics of Publication


Proceedings will be submitted for indexation by:


footer