Artificial Intelligence and Optimization Techniques for Smart Information System Generations

Inbunden, Engelska, 2025

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Beskrivning

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 algorithmsPresents 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 roboticsDiscusses artificial intelligence and optimization techniques for geographic information system (GIS) generation such as spatial data processingCovers artificial intelligence algorithms such as dimensionality, distance metrics, clustering, error calculation, hill climbing, and linear regressionIllustrates topics such as image recognition, natural language processing, fraud detection, information system security, and intrusion detection system

Produktinformation

Utgivningsdatum:2025-03-27
Mått:156 x 234 x 22 mm
Vikt:640 g
Format:Inbunden
Språk:Engelska
Serie:Future Generation Information Systems
Antal sidor:304
Förlag:Taylor & Francis Ltd
ISBN:9781032717036

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Mer om författaren

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.

Innehållsförteckning

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