There is no doubt that the semiconductor industry is in an era of rapid and profound transformation, driven by an increasing ...

Abstract: An unsupervised deep learning framework is proposed for solving 2-D electromagnetic inverse scattering problems (ISPs) with either full- or phaseless-data (PD), featuring good accuracy, ...

Struggling with microseismic signal classification in deep underground engineering? Researchers from Sichuan University ...

In 2026, choosing an AI track is mostly a decision about outcomes. GenAI programs help you ship faster workflows and software ...

We propose an unsupervised, annotation-free method to detect key cardiac phases—end-diastole (ED) and end-systole (ES)—from echocardiography videos. Our method learns interpretable motion trajectories ...

The following represents disclosure information provided by authors of this manuscript. All relationships are considered compensated unless otherwise noted. Relationships are self-held unless noted. I ...

Unsupervised learning is a branch of machine learning that focuses on analyzing unlabeled data to uncover hidden patterns, structures, and relationships. Unlike supervised learning, which requires pre ...

ABSTRACT: Aiming at the problems of well-developed dominant seepage channels, prominent viscous fingering phenomenon, complex dynamic evolution of flow fields, and difficulty in fine characterization ...

Quantifying natural behavior from video recordings is a key component in ethological studies. Markerless pose estimation methods have provided an important step toward that goal by automatically ...

The SVM identified loss of appetite, flank discomfort, abdominal bloating or gurgling, and pale or yellowish complexion as the most discriminative features. Unsupervised clustering revealed four ...