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Hidden Markov Model (HMM)

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Hidden Markov Model (HMM)  VIDEO LINK:  https://youtu.be/YIGCWNG8BIA A Hidden Markov Model (HMM) is a statistical model in which the system has hidden states that cannot be directly observed, but produce observable outputs. It is based on the Markov property, meaning the next state depends only on the current state. Video Chapters: HMM in Artificial Intelligence 00:00 Introduction 00:31 Statistical Model 00:54 HMM Examples 02:30 HMM 03:10 HMM Components 05:23 Viterbi Algorithm 06:23 HMM Applications 06:38 HMM Problems 07:28 HMM in Handwriting Recognition 11:20 Conclusion  HMM COMPONENTS A Hidden Markov Model (HMM) is a statistical model in which the system has hidden states that cannot be directly observed, but produce observable outputs. It is based on the Markov property, meaning the next state depends only on the current state. An HMM consists of states, observations, transition probabilities, emission probabilities, and initial probabilities. It is commonly used in a...
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Local Directional Pattern (LDP)

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 Local Directional Pattern How to Calculate Local Directional Pattern (LDP) Code? With Example |Kirsch Compass Mask| ~xRay Pixy Click here - >  WATCH NOW What are Local Directional Patterns? LDP = Local Directional Pattern. Local Directional Pattern is a descriptor i.e., used for Face Recognition.  What is Descriptor?  Descriptors rely on Gradient-based or intensity variation approaches 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). Local Directional Pattern ( LDP) Assign code for each pixel in the image.  Local Directional Pattern ( LDP) encoded image is divided into regions. How LDP Calculate?  For Each pixel in the image LDP computes an 8-bit binary code. 8-bit binary pattern is calculated by involving the lo...
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