Tole combines ultrasound and AI to improve motor neuron disease diagnosis, reducing reliance on invasive procedures.

A new study developed a snore-source classification model that uses STFT spectrograms, pretrained CNN features, and an L2-regularized SVM to identify where snoring originates in the upper airway.

Implementation of the MCNN-14 model for fashion image classification, achieving 93.08% accuracy on Fashion-MNIST. Based on our paper “An Efficient Multiple Convolutional Neural Network Model (MCNN-14) ...

Abstract: The domain of image classification has been seen to be dominated by high-performing deep-learning (DL) architectures. However, the success of this field, as seen over the past decade, has ...

Neural networks (NNs) have emerged as a powerful paradigm across diverse scientific and technological domains, instigating transformative advancements in areas such as drug discovery, image processing ...

Abstract: Deep neural network (DNN) belongs to an important class of machine learning algorithms generally used to classify digital data in the form of image and speech recognition. The computational ...

This project involves the classification of handwritten digits using three different classifiers: Linear Discriminant Analysis (LDA), Support Vector Machines (SVM), and Decision Trees. The goal is to ...