Abstract: Automatic underground object classification based on deep learning (DL) has been widely used in ground penetrating radar (GPR) fields. However, its excellent performance heavily depends on ...

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 ...

MORGANTOWN, Pa. - The Trump administration says it is focused on protecting unaccompanied migrant children. It imposed strict new background checks on those seeking custody of young migrants and cut ...

What is supervised learning and how does it work? In this video/post, we break down supervised learning with a simple, real-world example to help you understand this key concept in machine learning.

Lev Facher covers the U.S. addiction and overdose crisis. OnPoint NYC, the nonprofit that was the first in the nation to openly offer supervised drug consumption services, celebrated its fourth ...

Abstract: Network traffic classification (NTC) is vital for efficient network management, security, and performance optimization, particularly with 5G/6G technologies. Traditional methods, such as ...

The goal of a machine learning binary classification problem is to predict a variable that has exactly two possible values. For example, you might want to predict the sex of a company employee (male = ...

Researchers report that springing forward or falling back does not lead to spikes in heart attacks, easing concerns for patients and health systems alike. Study: Daylight Savings Time and Acute ...