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DeLTA 2021 will be held in conjunction with ICSOFT 2021, DATA 2021, ICINCO 2021 and SIMULTECH 2021.
Registration to DeLTA allows free access to the ICSOFT, DATA, ICINCO and SIMULTECH conferences (as a non-speaker).


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


Ana FredInstituto de Telecomunicações and University of Lisbon, Portugal
Carlo SansoneUniversity of Naples Federico II, Italy

Keynote Speakers

Matias Carrasco KindUniversity Illinois Urbana Champaign, United States
Fabio ScottiUniversita degli Studi di Milano, Italy
Elisabeth AndréUniversity of Augsburg, Germany
Petia RadevaUniversitat de Barcelona, Spain

Science and Technology Publications, Lda

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

Communications in Computer and Information Science

It is planned to publish a short list of revised and
extended versions of presented papers with
Springer in a CCIS Series book

In Cooperation with:

Proceedings will be submitted for evaluation for indexing by: