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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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What is Cathode Ray Tube ?

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 Display Devices:  Display devices are also known as Output devices. A commonly used output device in a graphics system is Video Monitor. The operations of most video monitors is based on the Cathode Ray Tube Design.  Cathode Ray Tube [CRT] CRT: Simplest version of CRT consists of a gas-filled glass tube in which two metal plates that is Cathode and Anode have placed. When a large voltage is placed across the electrodes, the Neutral Gas inside the Gas Tube Ionize into conducting plasma, and the current will flow as electrons travel from Cathode to the other side. CRT is a type of Display Device.  CRT are special electronic vacuum tubes that use a focused electron beam to Display Images.  Where Cathode Ray Tubes are Used? Television. Computers. Oscilloscopes. Radar Display. In video games Equipment. What is inside Cathode Ray Tubes? A CRT has a negatively charged terminal (i.e., Heated Filament).  The filament is contained inside a vacuum with a glass tube....
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How to Detect Masked Face from Digital Images using Viola Jones Algorithm.

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  How to Detect Masked Face from Digital Images using Viola Jones Algorithm.  Source Code : I = imread('4.jpg'); faceDetector = vision.CascadeObjectDetector; bboxes = step(faceDetector, I); IFaces = insertObjectAnnotation(I, 'rectangle', bboxes, 'Face'); figure imshow(IFaces), title('Detected faces'); Output: Video Link:  https://www.youtube.com/watch?v=bgnb8kLhoWs #faceDetection #imageProcessing #matlab
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