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
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.