Abstract: The cost of getting quality images and the cost of expertise which view these images have created barriers in medical imaging applications. Often, supervised machine learning approaches ...

First, we pretrained the encoder of a transformer-based network using a self-supervised approach on unlabeled abdominal computed tomography images. Subsequently, we fine-tuned the segmentation network ...

ABSTRACT: Foot-and-Mouth Disease (FMD) remains a critical threat to global livestock industries, causing severe economic losses and trade restrictions. This paper proposes a novel application of ...

In this tutorial, we explore the power of self-supervised learning using the Lightly AI framework. We begin by building a SimCLR model to learn meaningful image representations without labels, then ...

In the published article, there was an error in the Funding statement. The Funding statement was erroneously omitted, and financial support grants should have instead ...

ABSTRACT: Accurate prediction of malaria incidence is indispensable in helping policy makers and decision makers intervene before the onset of an outbreak and potentially save lives. Various ...

Supervised Learning - Classification: Analyze the data of INN Hotels to find which factors have a high influence on booking cancellations, build a predictive model that can predict which booking is ...

Leibniz-Centre for Agricultural Landscape Research (ZALF) e.V. Email: stefan [dot] stiller [at] zalf [dot] de, stillsen [at] gmail [dot] com This repository contains the code for the study ...

Colorectal cancer is the third most common cancer worldwide, and accurate pathological diagnosis is crucial for clinical intervention and prognosis assessment. Although deep learning has shown promise ...

Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, Michigan 48109, United States ...

Abstract: In this study, we propose an innovative dynamic classification algorithm aimed at achieving zero missed detections and minimal false positives, critical in safety-critical domains (e.g., ...