The International Conference on Deep Learning, Big Data and Blockchain (Deep-BDB 2021)

The role of deep learning for the analysis and learning of massive amounts of data from all aspects of daily-life has dramatically changed over the last few years. It is increasingly helping uncover trends leading to great successes. This book includes a collection of research manuscripts presenting state-of-the-art work in the areas of deep learning, blockchain and big data. All the manuscripts included in this book have been peer-reviewed based on aspects of novelty, originality and rigour. The main topics covered in the book include machine learning and time series, blockchain technologies and applications, data security, deep learning, and Internet of Things.

Sommario

Chapter 1: This book covers machine learning and time series, blockchain technologies and applications, data security, deep learning and Internet of Thing.- Chapter 2: A three-step machine learning pipeline for detecting and explaining anomalies in the time series of industrial process plants.- Chapter 3: Detecting Phishing Websites using Neural Network and Bayes Classifier.- Chapter 4: A Blockchain Framework for On-demand Intermodal Interlining: Blocklining.- Chapter 5: Intersection of AI and Blockchain Technology: Concerns and Prospects.

Dettagli sul prodotto

• Con la collaborazione di: Markus Aleksy (Editore), Irfan Awan (Editore), Salim Benbernou (Editore), Salima Benbernou (Editore), MUHAMMAD YOUNAS (Editore), Muhammad Younas et al (Editore)
• Editore: Springer, Berlin
• Lingue: Inglese
• Formato: Tascabile
• Pubblicazione: 14.09.2021
• EAN: 9783030843366
• ISBN: 978-3-0-3084336-6
• Pagine: 175
• Dimensioni: 155 mm x 10 mm x 235 mm
• Illustrazioni: XI, 175 p. 66 illus., 38 illus. in color.
• Serie: Lecture Notes in Networks and Systems
• Categoria: Scienze naturali, medicina, informatica, tecnica > Tecnica > Tematiche generali, enciclopedie