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A context-aware approach for long-term behavioural change detection and abnormality prediction in ambient assisted living
(
Elsevier
, 2015 , Article)
This research aims to describe pattern recognition models for detecting behavioural and health-related changes in a patient who is monitored continuously in an assisted living environment. The early anticipation of anomalies ...
Deep learning and cultural heritage: The CEPROQHA project case study
(
Institute of Electrical and Electronics Engineers Inc.
, 2019 , Conference Paper)
Cultural heritage takes an important part of the history of humankind as it is one of the most powerful tools for the transfer and preservation of moral identity. As a result, these cultural assets are considered highly ...
Digital heritage enrichment through artificial intelligence and semanticweb technologies
(
Institute of Electrical and Electronics Engineers Inc.
, 2019 , Conference Paper)
Art and culture represent substantial ways to transfer the history of humans across civilizations and epochs. Preserving artwork and cultural objects is thus important and the focus of multiple institutions and governments ...
Digitization and preservation of cultural heritage products
(
Springer New York LLC
, 2017 , Conference Paper)
Cultural heritage encompasses various aspects of a nation's history. Cultural heritage artifacts are considered as priceless items that need special care. Since the wide adoption of new digital technologies, documenting ...
Higher education internationalization: The Erasmus-Mundus network added value
(
Institute of Electrical and Electronics Engineers Inc.
, 2014 , Conference Paper)
Higher education internationalization can play a major role in developing universities and students' capacities and their opportunities broadly throughout the world. Irrespective of contextual differences within and between ...
A survey of clustering algorithms for big data: Taxonomy and empirical analysis
(
IEEE Computer Society
, 2014 , Article)
Clustering algorithms have emerged as an alternative powerful meta-learning tool to accurately analyze the massive volume of data generated by modern applications. In particular, their main goal is to categorize data into ...