Anang Muhamad Amin, Asad Khan, Benny Nasution

Internet-Scale Pattern Recognition (eBook, PDF)

New Techniques for Voluminous Data Sets and Data Clouds

• Format: PDF

Produktbeschreibung

For machine intelligence applications to work successfully, machines must perform reliably under variations of data and must be able to keep up with data streams. Internet-Scale Pattern Recognition: New Techniques for Voluminous Data Sets and Data Clouds unveils computational models that address performance and scalability to achieve higher levels

---

Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.

Produktdetails

• Verlag: Taylor & Francis
• Seitenzahl: 197
• Erscheinungstermin: 20. November 2012
• Englisch
• ISBN-13: 9781466510975
• Artikelnr.: 40066978

Autorenporträt

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.

Inhaltsangabe

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.