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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...

3D Translation Example

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 Consider the effect of a translation in the x,y,z direction by -2, -4, and -6 respectively on the homogenous coordinate position vectors [1, 6, 4].  Solution. 3D Translation Matrix is given as: Here, Tx = -2, Ty = -4, and Tz = -6. As We know, 3D translation is performed as: Therefore, we got  New co-ordinates are [-1  2  -2 ]

Three Dimensional Transformations and Viewing

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 Three Dimensional Transformations  Q. What is 3D Translation? A. Translation means shifting a point or moving the whole object. In 3D we need 3 Translatio factors. Translation Matrix for 3D:  Q. How to perform 3D Transformation? A.  To perform 3D Transformation. Multiply point with translation Matrix. Here, Q. What is 3D Scaling? A. Scaling changes the size of the object. Scaling in 3D is similar to scaling in 2D. The Matrix for 3D scaling transformation given as:
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