Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
612-822-4611

  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Search Techniques in Intelligent Classification Systems

Search Techniques in Intelligent Classification Systems

Savchenko, Andrey V.

Paperback

Series: Springerbriefs in Optimization

Technology & EngineeringGeneral ComputersGeneral Mathematics

ISBN10: 3319305131
ISBN13: 9783319305134
Publisher: Springer Nature
Published: May 12 2016
Pages: 82
Weight: 0.33
Height: 0.20 Width: 6.14 Depth: 9.21
Language: English

A unified methodology for categorizing various complex objects is presented in this book. Through probability theory, novel asymptotically minimax criteria suitable for practical applications in imaging and data analysis are examined including the special cases such as the Jensen-Shannon divergence and the probabilistic neural network. An optimal approximate nearest neighbor search algorithm, which allows faster classification of databases is featured. Rough set theory, sequential analysis and granular computing are used to improve performance of the hierarchical classifiers. Practical examples in face identification (including deep neural networks), isolated commands recognition in voice control system and classification of visemes captured by the Kinect depth camera are included. This approach creates fast and accurate search procedures by using exact probability densities of applied dissimilarity measures.

Also in

General Mathematics

View All