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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

Local Directional Pattern (LDP)

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 Local Directional Pattern How to Calculate Local Directional Pattern (LDP) Code? With Example |Kirsch Compass Mask| ~xRay Pixy Click here - >  WATCH NOW What are Local Directional Patterns? LDP = Local Directional Pattern. Local Directional Pattern is a descriptor i.e., used for Face Recognition.  What is Descriptor?  Descriptors rely on Gradient-based or intensity variation approaches detect Local Features (e.g.,  Edges, Blobs and Regions).  BLOB = Binary Large Object (i.e., the region of the image). Descriptors such as HOG, SIFT, SURF (rely on local gradient computation).  Binary Descriptors such as BRISK, ORB or FREAK (rely on local intensity differences). Local Directional Pattern ( LDP) Assign code for each pixel in the image.  Local Directional Pattern ( LDP) encoded image is divided into regions. How LDP Calculate?  For Each pixel in the image LDP computes an 8-bit binary code. 8-bit binary pattern is calculated by involving the lo...
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