This project implements an Image Classification system using a Convolutional Neural Network (CNN). The system takes an input image, processes it through the CNN model, and classifies it into ...

As a new optical machine learning framework, the diffractive deep neural network (D2NN) has attracted much attention due to its advantages such as low power consumption, parallel computing, and fast ...

This paper investigates uncertainty quantification (UQ) techniques in multi-class classification of chest X-ray images (COVID-19, Pneumonia, and Normal). We ...

In the field of image classification, while algorithms perform well at recognizing objects, understanding their decision-making processes remains challenging and limiting the applicability in critical ...

CIFAR-10 problems analyze crude 32 x 32 color images to predict which of 10 classes the image is. Here, Dr. James McCaffrey of Microsoft Research shows how to create a PyTorch image classification ...

However, social images are special multi-label images. social image classification still has a lot of space for improvement. In one aspect, we find that many methods using CNN networks for ...

Accurate glioma classification is very important for treatment planning and prognosis prediction. The main purpose of this study is to design a novel effective algorithm for further improving the ...