Abstract: Network traffic classification solutions have increasingly adopted complex models to improve performance. Yet, we show that a simple 1-nearest neighbor classifier-using only a compact ...

Liver cancer, including hepatocellular carcinoma (HCC), is a leading cause of cancer-related deaths globally, emphasizing the need for accurate and early detection methods. LiverCompactNet classifies ...

While there are many different types of budgets, they all serve as a framework for how you will spend your future cash. Sometimes aspirational and sometimes rigid, budgets are often a work in progress ...

This study investigates the application of a deep learning model, YOLOv8-Seg, for the automated classification of osteoporotic vertebral fractures (OVFs) from computed tomography (CT) images. A ...

Predicting tropical cyclones (TCs) accurately is crucial for disaster mitigation and public safety. Although the forecasting accuracy of TC tracks has improved substantially in recent decades, ...

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. Figure 1 illustrates the overall workflow of the hyperspectral ...

This repository contains the implementation, benchmarks, and supporting tools for my MSc dissertation project: Self-learning Variational Autoencoder for EEG Artifact Removal (Key code only). Benchmark ...

Deep learning is an AI function and a subset of machine learning, used for processing large amounts of complex data. Deep learning can automatically create algorithms based on data patterns.

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 ...

Abstract: Due to the limitations of collection conditions and costs, public brain network datasets generally combine data from multiple sites. However, the difference among multi-source data collected ...