MNIST Digit Classifier - Deep Learning Web Application A handwritten digit classification system using Deep Neural Networks (DNN) deployed as an interactive Streamlit web application. Status: Ready to ...

Bangla Handwritten Character Recognition (BHCR) remains challenging due to complex alphabets, and handwriting variations. In this study, we present a comparative evaluation of three deep learning ...

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• Architecture: 4-layer CNN (convolutional layers with 32, 64, 128, and 256 filters) → Max pooling → Dropout → Fully connected layers. • Training: Dataset: MNIST (28×28 grayscale digits).

Abstract: Handwritten digit recognition plays a crucial role in applications like automated form processing and character recognition software. This study explores how well the traditional K-Nearest ...

Abstract: In the application area of postal automation to signature verification, the Handwritten digit recognition (HRD) is major challenging field in the era of pattern recognition and machine ...