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Nash Equilibrium In Game Theory ~xRay Pixy

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 Video Link  CLICK HERE... Learn Nash Equilibrium In Game Theory Step-By-Step Using Examples. Video Chapters: Nash Equilibrium  00:00 Introduction 00:19 Topics Covered 00:33 Nash Equilibrium  01:55 Example 1  02:30 Example 2 04:46 Game Core Elements 06:41 Types of Game Strategies 06:55  Prisoner’s Dilemma  07:17  Prisoner’s Dilemma Example 3 09:16 Dominated Strategy  10:56 Applications 11:34 Conclusion The Nash Equilibrium is a concept in game theory that describes a situation where no player can benefit by changing their strategy while the other players keep their strategies unchanged.  No player can increase their payoff by changing their choice alone while others keep theirs the same. Example : If Chrysler, Ford, and GM each choose their production levels so that no company can make more money by changing their choice, it’s a Nash Equilibrium Prisoner’s Dilemma : Two criminals are arrested and interrogated separately. Each has two ...
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Face Recognition using Local Binary Patterns (LBP) [2/2] ~xRay Pixy

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Face Recognition Using Local Binary Pattern (LBP)


Multi-Block LBP is popular in texture recognition and is used for facial features extraction and detection has been used. The local binary operator is used for the calculation of binary patterns in digital images. The extracted features of the input images are displayed using the binary image. Binary images used two-pixel values and color black and white. The calculation of the local binary pattern is shown in Figure 3. A comparison of every neighboring pixel is done with the center pixel is done. If the neighbor pixel value is greater or equal (>=) to the center pixel value than we will assign 1 and if the neighbor pixel is smaller (<) than the central pixel than assign 0. Steps to calculate the binary patterns for face facial feature extraction and face detection are given below:
Algorithm:

Multi-Block LBP is used to encode the rectangular region’s intensity by using local binary patterns. Local Binary Pattern (LBP) looks at nine pixels at a time (i.e., 3x3 window of image = 9-pixel values and 2^9 = 512 possible values). By using Local Binary Pattern we can turn this 3x3 matrix into a single value. LBP focus on the very local neighborhood like 3x3. Multi-block LBP has been used for the large-scale structure. With the help of Multi-Block Local Binary Pattern (MB-LBP), 256 types of different binary patterns can be formed for edge detection and face detection from still images.

Face Recognition Using Local Binary Pattern (LBP)
Local Binary Pattern (LBP) Image Dataset Training for Face Recognition
Local Binary Pattern (LBP) Image Dataset Testing for Face Recognition
Local Binary Pattern (LBP) Feature Extraction, Local Binary Pattern (LBP) Histogram Construction.
Face Recognition using Local Binary Pattern (LBP) in MATLAB.

Local Binary Pattern (LBP) Videos | Projects

Local Binary Pattern (LBP) Image Dataset Training for Face Recognition [1/2] ~xRay Pixy

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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

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Bat algorithm Explanation Step by Step with example

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Grey Wolf Optimization Algorithm Numerical Example

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Whale Optimization Algorithm Code Implementation || WOA CODE || ~xRay Pixy

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