Internet-Scale Pattern Recognition (Hardcover)
Language: English
Published by Taylor & Francis Inc, Bosa Roca, 2012
- Hardcover
- New
Seller: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller
AbeBooks seller since June 22, 2007
Condition: New
£ 237.95
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Add to basketItem description from seller
Hardcover. 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 of reliability. It explores different ways of implementing pattern recognition using machine intelligence.Based on the authors research from the past 10 years, the text draws on concepts from pattern recognition, parallel processing, distributed systems, and data networks. It describes fundamental research on the scalability and performance of pattern recognition, addressing issues with existing pattern recognition schemes for Internet-scale data deployment. The authors review numerous approaches and introduce possible solutions to the scalability problem.By presenting the concise body of knowledge required for reliable and scalable pattern recognition, this book shortens the learning curve and gives you valuable insight to make further innovations. It offers an extendable template for Internet-scale pattern recognition applications as well as guidance on the programming of large networks of devices. This cutting-edge reference outlines the underlying theory and principles of efficient and effective distributed pattern recognition involving one-shot learning and in-network processing for different types of applications, including multimedia retrieval systems and event detection over different network environments. Investigating one-shot learning and in-network processing as complementary mechanisms for efficient and accurate distributed pattern analyses, it presents the technical aspects related to the development of scalable pattern recognition using a number of contemporary application development tools. It also considers scalability of pattern recognition schemes when dealing with such data. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…
Seller Inventory # 9781466510968
- Title
- Internet-Scale Pattern Recognition (Hardcover)
- Author
- Anang Muhamad Amin
- Publisher
- Taylor & Francis Inc, Bosa Roca
- Publication year
- 2012
- Condition
- new
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 146651096X
- ISBN 13
- 9781466510968
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 of reliability. It explores different ways of implementing pattern recognition using machine intelligence.
Based on the authors’ research from the past 10 years, the text draws on concepts from pattern recognition, parallel processing, distributed systems, and data networks. It describes fundamental research on the scalability and performance of pattern recognition, addressing issues with existing pattern recognition schemes for Internet-scale data deployment. The authors review numerous approaches and introduce possible solutions to the scalability problem.
By presenting the concise body of knowledge required for reliable and scalable pattern recognition, this book shortens the learning curve and gives you valuable insight to make further innovations. It offers an extendable template for Internet-scale pattern recognition applications as well as guidance on the programming of large networks of devices.
"Synopsis" may belong to another edition of this title.
About the Author
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.
"About the title" may belong to another edition of this title.
AussieBookSeller
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