The project titled "Medical Image Classification for Disease Diagnosis Using Convolutional Neural Networks" aims to develop a robust and accurate machine learning model for the automatic ...

BrainIAC, a breakthrough AI foundation model, is able to predict brain age, dementia, time-to-stroke, and brain cancer from brain magnetic resonance imaging (MRI).

Medical researchers at Mass General Brigham say the self-supervised foundational model can identify inherent features from ...

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...

Abstract: We introduce LCMatch, a novel semi-supervised scene classification framework designed to enhance the performance of remote sensing image classification. Our method improves upon the existing ...

Abstract: A novel approach is proposed in this study that combines superpixel (SP) segmentation and multiclassifier ensemble learning (EL) to address the limited availability of labeled samples in ...