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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

What is the difference between local descriptors and global descriptors?

Descriptors  rely on Gradient-based or intensity variation approaches to detect Local Features (e.g., Edges, Blobs, and Regions). BLOB = Binary Large Object (i.e., the region of the image). Descriptors such as HOG, SIFT, SURF (rely on local gradient computation). Binary Descriptors such as BRISK, ORB or FREAK (rely on local intensity differences) Global Descriptor –  Describe the whole image, Local Descriptor  – Describe the patch within the image. (The best example of the global descriptor is SIFT). LDP = Local Directional Pattern. Local Directional Pattern is a  descriptor  i.e., used for Face Recognition. How to Calculate Local Directional Pattern (LDP) Code?|Kirsch Compass Mask| https://youtu.be/dY0KarfWTV4
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