Product details:
| ISBN13: | 9783031348754 |
| ISBN10: | 3031348753 |
| Binding: | Paperback |
| No. of pages: | 367 pages |
| Size: | 235x155 mm |
| Language: | English |
| Illustrations: | 29 Illustrations, black & white; 104 Illustrations, color |
| 684 |
Category:
Intelligent Multimedia Signal Processing for Smart Ecosystems
Edition number: 2023
Publisher: Springer
Date of Publication: 3 October 2024
Number of Volumes: 1 pieces, Book
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EUR 192.59
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66 975 (63 786 HUF + 5% VAT )
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Short description:
A smart ecosystem is envisioned to exchange and analyze data across systems, enabling a flexible, faster, and reliable smart ecosystem for high-quality results at reduced costs and little human intervention. This book introduces many innovative approaches and provides solutions to various problems of smart ecosystems designed by employing various techniques/models based on AI, ML, Deep Learning, and the Internet of Things (IoT). The main focus is on intelligent multimedia processing and automated decision-making for various services, real-time data analysis, data security, cost-effective solutions for multimedia applications, smart information processing systems, and smart city planning to name a few. In addition, this book presents some key insights and future directions in the various areas of technology. Throughout the book, many state-of-the-art solutions concerning various applications are proposed to solve the issues and ensure the quality of services (QoS). The authors discuss the limitations of the current techniques used to design a smart ecosystem and highlight some prospective areas of research in the future. The book comprehensively discusses multimedia processing of various forms of data comprising text, images, and audio for the implementation of various solutions. The book is aimed to open many areas of research and thus would present a comprehensive reference for the design of smart ecosystems in various applications.
A smart ecosystem is envisioned to exchange and analyze data across systems, enabling a flexible, faster, and reliable smart ecosystem for high-quality results at reduced costs and little human intervention. This book introduces many innovative approaches and provides solutions to various problems of smart ecosystems designed by employing various techniques/models based on AI, ML, Deep Learning, and the Internet of Things (IoT). The main focus is on intelligent multimedia processing and automated decision-making for various services, real-time data analysis, data security, cost-effective solutions for multimedia applications, smart information processing systems, and smart city planning to name a few. In addition, this book presents some key insights and future directions in the various areas of technology. Throughout the book, many state-of-the-art solutions concerning various applications are proposed to solve the issues and ensure the quality of services (QoS). The authors discuss the limitations of the current techniques used to design a smart ecosystem and highlight some prospective areas of research in the future. The book comprehensively discusses multimedia processing of various forms of data comprising text, images, and audio for the implementation of various solutions. The book is aimed to open many areas of research and thus would present a comprehensive reference for the design of smart ecosystems in various applications.
Long description:
A smart ecosystem is envisioned to exchange and analyze data across systems, enabling a flexible, faster, and reliable smart ecosystem for high-quality results at reduced costs and little human intervention. This book introduces many innovative approaches and provides solutions to various problems of smart ecosystems designed by employing various techniques/models based on AI, ML, Deep Learning, and the Internet of Things (IoT). The main focus is on intelligent multimedia processing and automated decision-making for various services, real-time data analysis, data security, cost-effective solutions for multimedia applications, smart information processing systems, and smart city planning to name a few. In addition, this book presents some key insights and future directions in the various areas of technology. Throughout the book, many state-of-the-art solutions concerning various applications are proposed to solve the issues and ensure the quality of services (QoS). The authors discuss the limitations of the current techniques used to design a smart ecosystem and highlight some prospective areas of research in the future. The book comprehensively discusses multimedia processing of various forms of data comprising text, images, and audio for the implementation of various solutions. The book is aimed to open many areas of research and thus would present a comprehensive reference for the design of smart ecosystems in various applications.
Table of Contents:
Part 1: Smart Ecosystems: Opportunities and Challenges .- 1. Smart Ecosystems for Sustainable Development: Opportunities, Challenges, and Solutions through Research and Innovation.- 2. Big Data in Smart Ecosystems: Trends, Challenges and Future Prospectus.- 3. Breakthroughs and challenges in multimedia privacy and security in the Internet of Things (IoT).- 4. Analysis of Ensemble Methods for Phishing Detection.- Part II Intelligent Signal Processing for Smart Health.- 5. Machine Learning Based Diabetic Retinopathy Detection and Classification.- 6. CNN-SVM with Data Augmentation for Robust Blur Detection of Digital Breast Tomosynthesis Images.- 7. Lung Lesion Identification Using Geometrical Feature and Optical flow Method from Computed Tomography Scan Images.- 8. Performance Improvement with Optimization Algorithm in Isolating Left Ventricle and Non-Left Ventricle Cardiac.- 9 Dual-Feature CNN-SVM method for breast mass tissue abnormality classification ondigital mammography images adapted to breast density.- 10. Deterministic Seir Mathematical Model For Infectious Diseases Like Covid-19.- Part III Intelligent Signal Processing for Smart Industry.- 11. Detection of Power Distribution Fault in Thermal Images Using CNN.- 12. Text to Speech Synthesis using Deep Learning.- 13. Advanced Sequence Learning Approaches for Emotion Recognition Using Speech Signals.- 14. Comparison of Deep Learning Model Performance for Handwritten Character Recognition of School Children.- 15. Handwritten Urdu Recognition using BERT with Vision Transformers.
