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Markov Chains || Step-By-Step || ~xRay Pixy

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Learn Markov Chains step-by-step using real-life examples. Video Chapters: Markov Chains 00:00 Introduction 00:19 Topics Covered 01:49 Markov Chains Applications 02:04 Markov Property 03:18 Example 1 03:54 States, State Space, Transition Probabilities 06:17 Transition Matrix 08:17 Example 02 09:17 Example 03 10:26 Example 04 12:25 Example 05 14:16 Example 06 16:49 Example 07 18:11 Example 08 24:56 Conclusion
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MATLAB Code for Nose Detection

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Face Detection Systems are used for the identification of a person from digital images. The face detection system can extract the different facial features from a digital image. A set of facial features extracted from a digital image includes eyes, nose, mouth and face region. Face recognition is a difficult task due to the different facial expressions. With the help of a face detection system presence of a human face can be detected easily. For the detection of different facial features, the Viola-Jones algorithm is used in the proposed work. To make the task more manageable, Viola-Jones requires full view frontal upright faces.

Watch Video:  Nose Detection
Facial FEATURES: In any recognition system, the selection of feature extraction plays a vital role. There are a lot of feature extraction techniques proposed efficiency of the proposed system is not acceptable due to the lack of appropriate feature selection.
MATLAB CODE: -

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PARTICLE SWARM OPTIMIZATION ALGORITHM NUMERICAL EXAMPLE

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how is the LBP |Local Binary Pattern| values calculated? Step-by-Step with Example

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PSO Python Code || Particle Swarm Optimization in Python || ~xRay Pixy

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Grey Wolf Optimization Algorithm Numerical Example

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