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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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How Digital Image is formed? ~xRay Pixy

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Digital Image is Made up of Pixels. Pixel is the Smallest Element of an Image. A digital image is composed of a finite number of elements, each element has a particular location and value.
The digital image is a 2-dimensional function. It is represented by f(x,y). Where x,y is the plane coordinates, and f is the amplitude that is the brightness of the image. The sensor is used to sense the object structure and a continuous voltage signal is generated.
In order to create a digital image, we need to convert data into digital form. For this Sampling and Quantization is done.
Sampling is digitizing the coordinate value.
Quantization is analog to digital conversion of a sampled image to a finite number of gray level.
The process of digital image formation is shown in this video.
https://youtu.be/pNl-yhlp5bo

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PARTICLE SWARM OPTIMIZATION ALGORITHM NUMERICAL EXAMPLE

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Cuckoo Search Algorithm for Optimization Problems

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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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