Submission Deadline: March 02, 2022

https://delta.scitevents.org

July 12 – 14, 2022

Lisbon, Portugal

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.

DeLTA is organized in 5 major tracks:
1 – Models and Algorithms
2 – Machine Learning
3 – Big Data Analytics
4 – Computer Vision Applications
5 – Natural Language Understanding

Conference Chair(s)
Oleg Gusikhin, Ford Motor Company, United States
Kurosh Madani, University of Paris-EST Créteil (UPEC), France

Program Chair(s)
Ana Fred, Instituto de Telecomunicações and University of Lisbon, Portugal
Carlo Sansone, University of Naples Federico II, Italy

Proceedings will be submitted for indexation by:
SCOPUS
Google Scholar
The DBLP Computer Science Bibliography
Semantic Scholar
Microsoft Academic
Engineering Index (EI)
Web of Science / Conference Proceedings Citation Index

All papers presented at the conference venue will also be available at the SCITEPRESS Digital Library.

Kind regards,
Ana Rita Paciência
DeLTA Secretariat

Address: Av. S. Francisco Xavier Lote 7 Cv. C, Setubal 2900-616, Portugal
Tel: +351 265 520 185
Web: https://delta.scitevents.org
e-mail: delta.secretariat@insticc.org