By mastering two foreign languages, spearheading charity initiatives, and excelling academically, a Hanoi high-school student ...

Abstract: The conditional random field (CRF) model is suitable for the image segmentation because this model relaxes the assumption of conditional independence of the observed data and models the data ...

To generate unconditional samples, please run the UnconditionalDiffusionTraining_and_Generation/scripts/inference.py script python UnconditionalDiffusionTraining_and ...

Precisely predicting interactions between diverse biomolecules, including small molecules, peptides, and nucleic acids, is fundamental to drug design. We developed SiteAF3, a generalized, ...

Driver drowsiness or fatigue is among the most important factors that cause traffic accidents; therefore, a monitoring system is necessary to detect the state of a driver drowsiness or fatigue. In ...

Abstract. Interactive human motions and the continuously changing nature of intentions pose significant challenges for human trajectory prediction. In this paper, we present a neuralized Markov random ...

Myocardial perfusion MRI is important for diagnosing coronary artery disease, but current clinical methods face challenges in balancing spatial resolution, temporal resolution, and slice coverage.

Adam Hayes, Ph.D., CFA, is a financial writer with 15+ years Wall Street experience as a derivatives trader. Besides his extensive derivative trading expertise, Adam is an expert in economics and ...

Abstract: Pixel-level labelling tasks, such as semantic segmentation, play a central role in image understanding. Recent approaches have attempted to harness the capabilities of deep learning ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. As a supervised machine learning algorithm, conditional random fields are mainly used ...