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DeLTA 2024 : 5th International Conference on Deep Learning Theory and Applications | |||||||||||||||
Link: https://delta.scitevents.org | |||||||||||||||
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Call For Papers | |||||||||||||||
CALL FOR PAPERS
5th International Conference on Deep Learning Theory and Applications (DeLTA) Submission Deadline: February 15, 2024 Endorsed by: International Association for Pattern Recognition In Cooperation with: ACM Special Interest Group on Artificial Intelligence Association for the Advancement of Artificial Intelligence International Neural Network Society European Society for Fuzzy Logic and Technology Proceedings will be submitted for evaluation for indexation by: DBLP Google Scholar EI-Compendex INSPEC Japanese Science and Technology Agency (JST) Norwegian Register for Scientific Journals and Series Mathematical Reviews SCImago Scopus zbMATH Web of Science / Conference Proceedings Citation Index The event will be of hybrid nature, in the sense that online presentations of accepted papers will be possible for those authors that are unable to travel to the venue. https://delta.scitevents.org July 10 - 11, 2024 Dijon, France --------- Scope: 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: Machine Learning Models and Algorithms Big Data Analytics Computer Vision Applications Natural Language Understanding Conference Chair(s) Carlo Sansone, University of Naples Federico II, Italy Oleg Gusikhin, Ford Motor Company, United States Program Chair(s) Ana Fred, Instituto de Telecomunicações and Instituto Superior Técnico (University of Lisbon), Portugal Allel Hadjali, LIAS/ENSMA, Poitiers, France Program Committee https://delta.scitevents.org/ProgramCommittee.aspx DeLTA Secretariat delta.secretariat@insticc.org Address: Avenida de S. Francisco Xavier, Lote 7 Cv. C, Setubal 2900-616, Portugal Tel:+351 265 520 185 Web: https://delta.scitevents.org |
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