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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