In this project, a variety of machine learning models, including Support Vector Machines (SVM), k-Nearest Neighbors (k-NN), Logistic Regression, Decision Trees, and Random Forest Classifier, were ...

Classify a given image of handwritten ... the overall shape of the digit. Classification: The extracted features are fed into a machine learning model that has been trained to recognize digits. Common ...

Abstract: The task for handwritten digit recognition has been troublesome due to various variations in writing styles. Therefore, we have tried to create a base for future researches in the area so ...

Abstract: Offline handwritten digit recognition is a well-known problem that remains at best partially solved. This paper presents a study of three different algorithms for offline handwritten ...

The MNIST is a dataset developed by LeCun, Cortes and Burges for evaluating machine learning models on the handwritten digit classification problem [11] . It has been widely used in research and to ...