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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...

Viewing Pipeline - 2 Dimensional Viewing in Computer Graphics

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 Viewing Pipeline: Viewing Transformation in several steps: 1. Modeling Coordinates 2. World Coordinate System 3. Clipping Window 4. Normalize - Normalized Coordinates  5. Device Coordinate  6. ViewPort 7. Clipping First, we construct the scene in the world coordinates using the output primitives. Next, obtain a particular orientation for the window, we can set up a 2D viewing coordinate plane and define windows in the viewing coordinate system. The viewing coordinate reference frame is used to provide a method for setting up arbitrary orientations for a rectangular window.  Once the viewing reference frame is established. we can transform description in the world coordinate to viewing coordinates. After that define a viewport in normalized coordinates ( in the range from 0 to 1). 2D Viewing Pipeline can be achieved by the following steps:  1. Construct world coordinate scene using modeling coordinate transformation.  2. convert world coordinates to viewin...
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