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Bermuda Triangle Optimizer

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VIDEO LINK The Bermuda Triangle Optimizer (BTO) is a nature-inspired algorithm that simulates a gravity-like pull in the Bermuda Triangle to find optimal solutions. Learn Bermuda Triangle Optimizer (BTO) Step-By-Step using Examples. Video Chapters: Bermuda Triangle Optimizer (BTO) 00:00 Introduction 00:34 About the Bermuda Triangle 02:06 Bermuda Triangle Optimizer  05:44 BTO STEPS 09:30 BTO Advantages 10:17 BTO Limitations 10:42 BTO Applications 11:07 Conclusion Bermuda Triangle Optimizer || Step-By-Step || ~xRay Pixy Video Link:  https://youtu.be/bBnsd7BBttg #optimization #algorithm #metaheuristic #robotics #deeplearning #ArtificialIntelligence #MachineLearning #computervision #research #projects #thesis #Python #optimizationproblem #optimizationalgorithms 

What is Cathode Ray Tube ?

 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....

How to Detect Masked Face from Digital Images using Viola Jones Algorithm.

  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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