Artificial Intelligence and Optimization Techniques for Smart Information System Generations (eBook, ePUB)

Redaktion: Ali, Aleem; Alharbe, Nawaf; Chakraborty, Rajdeep

• Format: ePub

Produktbeschreibung

The text comprehensively focusses on the use of artificial intelligence and optimization techniques for creating smart information systems.

• Focuses on extracting information from blockchain repository using artificial intelligence and machine learning algorithms
• Presents deep learning models to identify and locate objects within images and videos, making it possible for machines to perform tasks such as self-driving cars, surveillance, and robotics
• Discusses artificial intelligence and optimization techniques for geographic information system (GIS) generation such as spatial data processing
• Covers artificial intelligence algorithms such as dimensionality, distance metrics, clustering, error calculation, hill climbing, and linear regression
• Illustrates topics such as image recognition, natural language processing, fraud detection, information system security, and intrusion detection system

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Produktdetails

• Verlag: Taylor & Francis eBooks
• Erscheinungstermin: 28. März 2025
• Englisch
• ISBN-13: 9781040312582
• Artikelnr.: 73440044

Autorenporträt

Aleem Ali is presently working as a professor, in the Department of Computer Science and Engineering, at Chandigarh University, Punjab, India. He has published more than forty research papers in journals and conferences of national and international repute. His areas of research interest include the Internet of Things, machine learning techniques, wireless networks, network security, cryptography, and data mining. Rajdeep Chakraborty is currently working as a professor, in the Department of Computer Science and Engineering, at Medi-Caps University, Indore, MP, India. He has more than twenty years of research and academic experience. He has publications in reputed international journals and conferences. He also has written an authored book on hardware cryptography. His field of interest is mainly in cryptography and computer security. Nawaf R. Alharbe is presently working as a professor, college of computer science and engineering, dept. of AI & DS, at Taibah University, Madinah, Saudi Arabia. He is an esteemed visiting professor, in the faculty of computing, engineering, and sciences, at Staffordshire University, United Kingdom. He has published research papers in journals and conferences of national and international repute. His areas of research interest include the Internet of Things, network communication, sensor technology, network security, wireless communications, computer networking, and cloud computing.

Inhaltsangabe

1. Unveiling the Power of Prediction: A Comprehensive Guide to Machine
Learning Techniques, from Data Preparation to Model Interpretability for
Early Prediction of Diabetes and Effective Management.
2. Digital Image Forgery Techniques for Smart Information Generations.
3. Artificial Intelligence(AI) and optimization for Health Information
System(HIS) generation.
4. Agricultural Information Systems emphasizing Agro Robots towards Digital
and Sustainable Agriculture.
5. Smart Agriculture based on Artificial Intelligence in Africa Region:
Open Challenges, Solutions.
6. Synergizing Artificial Intelligence and Optimization Techniques for
Enhanced Public Services.
7. Architectural Pattern for Implementing XAI as a Service for Container
Orchestrated Machine Learning Model Deployments.
8. Quantum Machine Learning (QML) Algorithms for Smart Biomedical
Applications.
9. Artificial Intelligence for Information System Security.
10. Optimized Image Recognition for Smart Information Generations: A
Comprehensive Evaluation of Image Processing Techniques.
11. Machine Learning based Security Algorithms for Cloud Computing: A
Comprehensive Survey.
12. Securing Information in Transit: Leveraging AI/ML for Robust Data
Protection.
13. Optimizing Medical Image Compression for Efficient Information System
Integration: A Comprehensive Review.
14. FaceTrack: A Face Recognition-based Real-time Attendance Marking
Approach using Haar Cascade and Machine Learning.
15. Optimizing Information Systems for Green Computing in Higher
Education: From Awareness to Action.
16. Evaluating Thin Client Solutions: A Sustainable and Energy-Efficient
Alternative to Traditional Classroom PCs