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Pattern recognition

All lectures: All lectures on the discipline: pattern recognition are collected here. These fascinating lectures provide us with the opportunity to explore the deep principles and phenomena underlying our knowledge and our desire to understand the world.


1. Analysis of existing approaches to face recognition
2. Determining the dominant colors in a picture in PHP using the k-means method and the method of suffering values
3. Intellect in Internet technologies. Recognition of images, speech, meaning
4. Convolutional neural network (convolutional neural network -CNN)
5. Neocognitron
6. Cognitron
7. Machine vision systems
8. Deconvolutional Neural Network (DNN)
9. Introduction to Title: Pattern Recognition Techniques
10. 1. Deterministic methods for solving recognition problems. Building decision rules. The method of building standards.
11. The method of fragmented standards. Linear decision rules
12. Nearest Neighbor Method. Potential function method
13. Structural (linguistic) methods
14. Cluster analysis in pattern recognition
15. Criteria informative signs. Selection of informative features
16. Statistical Pattern Recognition Techniques
17. Nearest Neighbor Method for Static Pattern Recognition
18. Nearest neighbor rule for static recognition
19. Parametric estimation of distributions
20. Likelihood Maximum Method
21. The case of statistically independent traits
22. Recognition with unknown prior probabilities of images
23. Neumann-Pearson criterion in pattern recognition
24. Sequential recognition procedures
25. Approximation method for estimating distributions by sample
26. taxonomy problem solving by statistical methods
27. Hierarchical recognition systems
28. UTILIZATION OF CELL AUTOMATIC SYSTEMS FOR TEXT RECOGNITION