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Retracted: MNIST Handwritten Digit Recognition using Machine Learning

Elizabeth Rani. G, M Sakthimohan, Abhigna Reddy. G, D Selvalakshmi., Thomalika Keerthi, Raja Sekar. R

20222022 2nd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE)41 citationsDOI

Abstract

Identification of the MNIST database that will be in handwritten digit can be recognized by the machine. It can be recognized that the human handwritten form into the machine language. Here we are using some machine learning algorithm that is Convolutional Neural Network (CNN). MNIST database consist of nine digits that is 0 to 9. It can be used to change over manually written digits into machine lucid arrangements. The primary target of this work is to guarantee successful and dependable methodologies for acknowledgment of written by hand digits and make banking tasks more straightforward and mistake free. The MNIST database will be identified by the machine very accurately. Here we are finding the handwritten digit accuracy.

Topics & Concepts

MNIST databaseComputer scienceDigit recognitionMistakeArtificial intelligenceConvolutional neural networkIdentification (biology)Numerical digitSpeech recognitionNumeral systemPattern recognition (psychology)Artificial neural networkHandwriting recognitionMachine learningFeature extractionArithmeticMathematicsLawBotanyBiologyPolitical scienceHandwritten Text Recognition TechniquesVehicle License Plate RecognitionHand Gesture Recognition Systems
Retracted: MNIST Handwritten Digit Recognition using Machine Learning | Litcius