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Video Link Multi-Block Local Binary Pattern || Calculate LBP Corner Pixel Values ||  https://youtu.be/o8qfJWQ_FG0  Local Binary Patterns (LBP) is a simple and efficient technique used in image processing to describe the texture or patterns within an image. LBP is widely used for applications like face recognition and texture classification since it is easy to compute and very effective at capturing the texture in photos.  Step How LBP WORKS:  For each pixel in the image, LBP looks at the pixel’s neighbors, typically the 8 pixels surrounding it in a 3x3 grid. LBP compares each of these neighboring pixels with the center pixel. If the neighboring pixel has a value greater than or equal to the center pixel, it's marked as 1; otherwise, it's marked as 0. This comparison forms a binary number for the pixel.  The binary number is then converted into a decimal value. This value represents the texture pattern at that pixel. By doing this for every pixel in the image, LBP creates a new

Pareto Optimal Solutions || Multi Objective Optimization Problems || ~xR...

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Learn how to calculate Pareto optimal solutions. Video Chapters: Pareto Optimality 00:00 Introduction 00:24 Pareto Optimality 02:33 Pareto Optimality Importance 03:29 Pareto Optimality Disadvantages 03:54 Pareto Optimality Applications 04:02 Example 1 Robot in Field 05:39 Steps to Calculate Pareto Optimality 07:41 Example 2 Math Example 11:03 Example 3 Resource Allocation Problem 16:09 Conclusion
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