This repository contains a handwritten digit recognition project using deep learning. The model is trained on datasets like MNIST to classify digits (0-9) with high accuracy.

The Milwaukee Police Department has not relied on evidence-based research in their decision to use facial recognition technology. Instead, they are disregarding research that unequivocally shows that ...

Abstract: This senior thesis develops a real-time handwritten digit identification system using a Raspberry Pi 3B+ with a camera module, leveraging a lightweight CNN optimized with MNIST. The project ...

The lawsuit alleges the company uses a form of artificial intelligence called “computer vision” to help mitigate theft by collecting data about customers’ facial geometry Jon Cherry/Bloomberg via ...

Deep neural networks (DNNs), the machine learning algorithms underpinning the functioning of large language models (LLMs) and other artificial intelligence (AI) models, learn to make accurate ...

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This project implements a CNN-based image classification model using the MNIST dataset to recognize handwritten digits from 0 to 9. It is built using TensorFlow, trained in Google Colab, and ...

Learn how to train a neural network to recognize hand-drawn digits using PyTorch! A fun and beginner-friendly intro to deep learning and computer vision. Home Depot raises red flag about customer ...

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