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DeLTA 2025 will be held in conjunction with ICSOFT 2025, DATA 2025, SIMULTECH 2025, ICSBT 2025 and SECRYPT 2025.
Registration to DeLTA allows free access to the ICSOFT, DATA, SIMULTECH, ICSBT and SECRYPT conferences (as a non-speaker).



Although the conference is back to the normal mode (i.e., in-person) speakers are allowed to present remotely if unable to travel to the venue (hybrid support).
 

Upcoming Submission Deadlines

Regular Paper Submission: January 17, 2025
Position/Regular Paper Submission: March 3, 2025

(See Important Dates for more information)
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 Co-chairs

Oleg GusikhinFord Motor Company, United States
Carlo SansoneUniversity of Naples Federico II, Italy

PROGRAM CO-CHAIRS

Allel HadjaliLIAS/ENSMA, Poitiers, France
Emanuele MaioranaRoma Tre University, Italy
 
Publications:
Communications in Computer and Information Science

The proceedings will be published by
Springer in a CCIS Series book

Endorsed by:

In Cooperation with:

Proceedings will be submitted for evaluation for indexing by:


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