Sustainable IoT and Data Analytics Enabled Machine Learning Techniques and Applications (Contributions to Environmental Sciences & Innovative Business Technology)

Sustainable IoT and Data Analytics Enabled Machine Learning Techniques and Applications (Contributions to Environmental Sciences & Innovative Business Technology)
by: V. Ajantha Devi (Editor)
Publisher: Springer
Edition: 2024th
Publication Date: 2024/9/28
Language: English
Print Length: 182 pages
ISBN-10: 9819753643
ISBN-13: 9789819753642
Book Description
This book provides a structured presentation of machine learning related to vision, speech, and natural language processing. It addresses the tools, techniques, and challenges of machine learning algorithm implementation, computation time, and the complexity of reasoning and modeling of different types of data. The book covers diverse topics such as semantic image segmentation, deep visual residual abstraction, brain–computer interfaces, natural language processing, traffic and signaling, driverless driving, and radiology. The majority of smart applications have a need for a sustainable Internet of things (IoT) and artificial intelligence. Active research trends and future directions of machine learning under big data analytics are also discussed. Machine learning is a class of artificial neural networks that have become dominant in various computer vision tasks, attracting interest across a variety of domains as they are a type of deep neural networks efficient in extracting meaningful information from visual imagery.
About the Author
This book provides a structured presentation of machine learning related to vision, speech, and natural language processing. It addresses the tools, techniques, and challenges of machine learning algorithm implementation, computation time, and the complexity of reasoning and modeling of different types of data. The book covers diverse topics such as semantic image segmentation, deep visual residual abstraction, brain–computer interfaces, natural language processing, traffic and signaling, driverless driving, and radiology. The majority of smart applications have a need for a sustainable Internet of things (IoT) and artificial intelligence. Active research trends and future directions of machine learning under big data analytics are also discussed. Machine learning is a class of artificial neural networks that have become dominant in various computer vision tasks, attracting interest across a variety of domains as they are a type of deep neural networks efficient in extracting meaningful information from visual imagery. Read more