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Classification and Detection of Acne on the Skin using Deep Learning Algorithms

Nikhil Pancholi, Silky Goel, Rahul Nijhawan, Siddharth Gupta

202123 citationsDOI

Abstract

Teenagers and young adults are prone to acne. It's a skin condition that arises when oil and dead skin cells clog hair follicles. The face, forehead, upper back, and chest are the most common places where it occurs. Excess bacteria, inflammation, and blocked hair follicles are all reasons that contribute to acne. It is the seventh epidemic and is thought to afflict 9.4% of the world's population. For the identification of acne on diverse skins, we used various pre-trained CNN models such as Inception V3, VGG16, and VGG19. We also used machine learning classifiers for a thorough examination of acne detection. The Inception v3 with the logistic regression classifier provides the best accuracy of 99.5%.

Topics & Concepts

AcneForeheadArtificial intelligenceClassifier (UML)Deep learningDermatologyComputer scienceLogistic regressionPopulationMedicinePattern recognition (psychology)Machine learningSurgeryEnvironmental healthDigital Media Forensic DetectionImage Processing Techniques and ApplicationsImbalanced Data Classification Techniques
Classification and Detection of Acne on the Skin using Deep Learning Algorithms | Litcius