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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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Detect Facial Feature using MATLAB

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Face Detection Systems are used for the identification of a person from digital images. The face detection system can extract the different facial features from a digital image. A set of facial features extracted from a digital image includes eyes, nose, mouth and face region. Face recognition is a difficult task due to the different facial expressions. With the help of a face detection system presence of a human face can be detected easily. For the detection of different facial features, the Viola-Jones algorithm is used in the proposed work. To make the task more manageable, Viola-Jones requires full view frontal upright faces.
Using this Matlab code you can: - Create your own face detection system - It is is easy and simple to understand.


MATLAB CODE FOR FACIAL FEATURE DETECTION

How to Detect Facial Feature using Matlab
The Algorithm used for face detection is the Viola-Jones algorithm. Different models are available for face recognition. These models can detect the face, eyes, and nose. But the detection process is very slow. To solve this problem, the viola-jones algorithm is applied to detect the different facial features. Viola-jones algorithm is to face and provides accurate results from the input digital image.

Facial FEATURES: In any recognition system, the selection of feature extraction plays a vital role. There are a lot of feature extraction techniques proposed efficiency of the proposed system is not acceptable due to the lack of appropriate feature selection.

VIDEO: How to Detect Facial Feature using Matlab

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