Abstract: This paper proposes a cascaded deep convolutional neural network (CNN) architecture consisting of a data pre-processing sub-network and a task-specific sub-network, forming a hierarchically ...

This group project explores the use of neural networks to model avalanche hazard forecasts using a 15-year dataset from the Scottish Avalanche Information Service (SAIS). Our group has been assigned ...

Deep neural networks (DNNs), the machine learning algorithms underpinning the functioning of large language models (LLMs) and other artificial intelligence (AI) models, learn to make accurate ...

This study retrospectively analyzed the multimodal ultrasound features and clinical characteristics of 586 patients with unexplained cervical lymphadenopathy who were treated at three hospitals ...

Abstract: Recent advances in hardware and software technology have made it possible to implement more resourcedemanding deep learning algorithms in constrained hardware environments. This creates ...

The scary thing about Dwight "D.J." Mims when it comes to coaching football - he has only scratched the surface. But now, he's found one of those rare jobs he can really establish his name by leading ...

ABSTRACT: The storage layer within the Moxizhuang Oilfield in the Junggar Basin develops various types of interlayer barriers with significant differences in morphology and scale of development. In ...

we implment a our own Neural Network Mini Library. In Part 2 of the project, we used PyTorch to create a Neural Network that predicts California House Prices. The python files are called ...