This project implements a neural network model for classifying ... techniques for image classification tasks. Approach--> Loaded and preprocessed the MNIST dataset (normalization, reshaping). Built a ...

This repository contains an end-to-end implementation of a convolutional neural network (CNN) trained on the CIFAR-10 dataset for multi-class image classification ... AutoAugment). Deploy model using ...

Alessandro Ingrosso, researcher at the Donders Institute for Neuroscience, has developed a new mathematical method in ...

Welcome to Learn with Jay – your go-to channel for mastering new skills and boosting your knowledge! Whether it’s personal ...

This model is based on "self-attention neural network," which can learn patterns and make accurate predictions. The model was trained using datasets generated by SuperMC, a sophisticated ...

Roshan Kenia presented a poster on how AI-CNet3D enhances glaucoma classification using cross-attention networks while ...

The ambiguity in medical imaging can present major challenges for clinicians who are trying to identify disease. For instance ...