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Avis sur Internet - Scale Pattern Recognition de Anang Muhamad Amin Format Relié - Livre Littérature Générale
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Présentation Internet - Scale Pattern Recognition de Anang Muhamad Amin Format Relié
- Livre Littérature Générale
Résumé : Based on the authors' research from the past 10 years, this book unveils computational models that address performance and scalability to achieve higher levels of reliability. Drawing on concepts from pattern recognition, parallel processing, distributed systems, and data networks, it explores different ways of implementing pattern recognition using machine intelligence. The authors offer an extendable template for Internet-scale pattern recognition applications as well as guidance on the programming of large networks of devices.
Biographie: Anang Hudaya Muhamad Amin is a senior lecturer in the Faculty of Information Science and Technology at Multimedia University in Malaysia. He received a BTech (Hons.) in information technology from Universiti Teknologi PETRONAS and a masters in network computing and PhD from Monash University. His research interests include artificial intelligence with specialization in distributed pattern recognition and bio-inspired computational intelligence, wireless sensor networks, and distributed computing. Asad I. Khan is a senior lecturer in the Faculty of Information Technology at Monash University. Dr. Khan is an Australian Research Council assessor and has published over 80 refereed papers. His research areas include parallel computation, neural networks, and distributed pattern recognition as well as the development of e-research systems and intelligent sensor networks. Benny Nasution is with the Department of Computer Engineering at Politeknik Negeri Medan. Dr. Nasution was awarded the IBM Award from Tokyo Research Lab and the Mollie Holman Medal from Monash University.
Sommaire: I Recognition: A New Perspective: Introduction. Distributed Approach for Pattern Recognition. II Evolution of Internet-Scale Recognition: One-Shot Learning Considerations. Hierarchical Model for Pattern Recognition. Recognition via a Divide-and-Distribute Approach. III Systems and Tools: Internet-Scale Applications Development. IV Implementations and Applications: Multi-Feature Classifications for Complex Data. Pattern Recognition within Coarse-Grained Networks. Event Detection within Fine-Grained Networks. Recognition: The Future and Beyond. Bibliography.