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Confusion Matrix with Real-Life Examples || Artificial Intelligence || ~...

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Learn about the Confusion Matrix with Real-Life Examples. A confusion matrix is a table that shows how well an AI model makes predictions. It compares the actual results with the predicted ones and tells which are right or wrong. It includes True Positive (TP), False Positive (FP), False Negative (FN), and True Negative (TN). Video Chapters: Confusion Matrix in Artificial Intelligence 00:00 Introduction 00:12 Confusion Matrix 03:48 Metrices Derived from Confusion Matrix 04:26 Confusion Matrix Example 1 05:44 Confusion Matrix Example 2 08:10 Confusion Matrix Real-Life Uses #artificialintelligence #machinelearning #confusionmatrix #algorithm #optimization #research #happylearning #algorithms #meta #optimizationtechniques #swarmintelligence #swarm #artificialintelligence #machinelearning
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What are the best algorithms for face detection in Matlab?

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The best algorithms for face detection in Matlab = Viola-Jones Algorithm
Face from the different digital images can be detected. The vision. CascadeObjectDetector uses the Viola-Jones algorithm to detect people’s Faces, Noses, Eyes, Mouth or upper body. The Cascade Object Detector build into MATLAB to detect the facial features from a digital image.
  • Detects the left and right eyes separately.
  • Detects the mouth.
  • Detect the objects using the viola jones algorithm.
  • Detect a pair of eyes.
  • Detects faces that are upright and forward-facing.
For Face detection:
faceDetector=vision.CascadeObjectDetector('FrontalFaceCART');
For Eyes detection:
faceDetector=vision.CascadeObjectDetector('EyePairBig’);
I Created a Face Detection system using Viola- Jones algorithm.
Book : Face and Facial Expression Recognition
LINK : Face Doctor - Viola Jones
LINK
Project | Face Detection using Polar Harmonic Transforms ~xRay Pixy

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