Badal Soni – författare

This book constitutes the refereed proceedings of the 5th International Conference on Machine Learning, Image Processing, Network Security and Data Sciences, MIND 2023, held in Hamirpur, India, during December 21–22, 2023. The 29 full papers included in this book were carefully reviewed and selected from 173 submissions.

This two-volume set (CCIS 1240-1241) constitutes the refereed proceedings of the Second International Conference on Machine Learning, Image Processing, Network Security and Data Sciences, MIND 2020, held in Silchar, India. The 79 full papers and 4 short papers were thoroughly reviewed and selected from 219 submissions.

This two-volume set (CCIS 1240-1241) constitutes the refereed proceedings of the Second International Conference on Machine Learning, Image Processing, Network Security and Data Sciences, MIND 2020, held in Silchar, India. The 79 full papers and 4 short papers were thoroughly reviewed and selected from 219 submissions.

By the end of the book, the readers will have an understanding of different deep learning approaches, models, pre-trained models, and familiarity with the implementation of various deep learning algorithms using various frameworks and libraries.

By the end of the book, the readers will have an understanding of different deep learning approaches, models, pre-trained models, and familiarity with the implementation of various deep learning algorithms using various frameworks and libraries.

This book presents a detailed study of key points and block-based copy-move forgery detection techniques with a critical discussion about their pros and cons. Five different image copy-move forgery detection techniques are implemented to overcome the limitations of existing copy-move forgery detection techniques.

This book presents a detailed study of key points and block-based copy-move forgery detection techniques with a critical discussion about their pros and cons. Five different image copy-move forgery detection techniques are implemented to overcome the limitations of existing copy-move forgery detection techniques.

This book constitutes the refereed proceedings of the Third International Conference on Machine Learning, Image Processing, Network Security and Data Sciences, MIND 2021. In addition to providing basic principles of data processing, this book teaches standard models and algorithms for data and image analysis.

This book constitutes the refereed proceedings of the Third International Conference on Machine Learning, Image Processing, Network Security and Data Sciences, MIND 2021. In addition to providing basic principles of data processing, this book teaches standard models and algorithms for data and image analysis.

This book features proceedings of the 2nd International Conference on Artificial Intelligence, Computing Technologies, Internet of Things (IoT), and Data Analytics – AICTA 2024.

This book provides an in-depth analysis of the design and implementation of a smartphone sensor-based Human Activity Recognition (HAR) system using advanced learning models. It offers detailed insights into key advancements and future directions for HAR system development. The content includes a comprehensive literature review on wearable sensor-based HAR, along with descriptions of publicly available datasets for building HAR systems. To overcome the limitations of existing sensor-based HAR systems, the book emphasizes the creation of a robust HAR dataset in uncontrolled environments. This dataset is developed using built-in smartphone sensors, enabling real-time activity classification. The book presents multiple effective and optimized classifiers for developing efficient HAR systems, leveraging both self-generated and publicly available data.The book demonstrates high effectiveness in real-time activity classification and addresses common challenges such as class imbalance and domain shift. It provides practical methodologies and techniques to enhance HAR system performance. This book is an essential resource for professionals, healthcare practitioners, academics, researchers, and students specializing in health applications, signal processing, machine learning, ensemble learning, and deep learning. It offers extensive analysis and actionable insights for investigators, helping streamline product development through intelligent learning algorithms in the field of Human Activity Recognition.

This book features proceedings of the 2nd International Conference on Artificial Intelligence, Computing Technologies, Internet of Things (IoT), and Data Analytics – AICTA 2024. The theme of the conference is “Artificial Intelligence and its applications.” It focuses on recent trends and innovative approaches in the different domains of Computer Engineering like cloud computing, image processing and computer vision, machine learning,g and deep learning, IoT and analytics, security, etc. The book introduces new ideas in artificial intelligence and its subset technologies like machine learning, deep neural networks, etc. This volume will be useful for researchers and practitioners working in computer engineering and related areas.