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The International Conference on Deep Learning, Big Data and Blockchain (DBB 2022)
Details
Deep and machine learning is the state-of-the-art at providing models, methods, tools and techniques for developing autonomous and intelligent systems which can revolutionise industrial and commercial applications in various fields such as online commerce, intelligent transportation, healthcare and medicine, etc. The ground-breaking technology of blockchain also enables decentralisation, immutability, and transparency of data and applications. This event aims to enable synergy between these areas and provide a leading forum for researchers, developers, practitioners, and professionals from public sectors and industries to meet and share the latest solutions and ideas in solving cutting-edge problems in the modern information society and the economy. The conference focuses on specific challenges in deep (and machine) learning, big data and blockchain. Some of the key topics of interest include (but are not limited to): Deep/Machine learning based models
Statistical models and learning
Data analysis, insights and hidden pattern
Data visualisation
Security threat detection
Data classification and clustering Blockchain security and trust Blockchain data management
Presents recent advances on deep learning, big data and blockchain Includes proceedings of the 3rd International Conference on Deep Learning, Big Data and Blockchain Written by experts in the field
Weitere Informationen
- Allgemeine Informationen
- GTIN 09783031160349
- Genre Technology Encyclopedias
- Auflage 1st edition 2023
- Editor Irfan Awan, Muhammad Younas, Jamal Bentahar, Salima Benbernou
- Lesemotiv Verstehen
- Anzahl Seiten 148
- Herausgeber Springer
- Größe H235mm x B155mm x T9mm
- Jahr 2022
- EAN 9783031160349
- Format Kartonierter Einband
- ISBN 3031160347
- Veröffentlichung 01.09.2022
- Titel The International Conference on Deep Learning, Big Data and Blockchain (DBB 2022)
- Untertitel Lecture Notes in Networks and Systems 541
- Gewicht 236g
- Sprache Englisch