The International Conference on Deep Learning, Big Data and Blockchain (Deep-BDB 2021) / edited by Irfan Awan, Salima Benbernou, Muhammad Younas, Markus Aleksy.

Format:

Book

Contributor:

Awan, Irfan, editor.

Series:

Lecture Notes in Networks and Systems, 2367-3389 ; 309

Language:

English

Subjects (All):

Computational intelligence.

Engineering--Data processing.

Engineering.

Big data.

Computational Intelligence.

Data Engineering.

Big Data.

Local Subjects:

Computational Intelligence.

Data Engineering.

Big Data.

Physical Description:

1 online resource (182 pages)

Edition:

1st ed. 2022.

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2022.

Summary:

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.

Contents:

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.

Notes:

Includes index.

ISBN:

3-030-84337-8