Abstract: A precise change detection in the multi-temporal optical images is considered as a crucial task. Although a variety of machine learning-based change detection algorithms have been proposed ...
Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...
Introduction Application of artificial intelligence (AI) tools in the healthcare setting gains importance especially in the domain of disease diagnosis. Numerous studies have tried to explore AI in ...
The third phase of ticket sales for the FIFA World Cup 2026, the Random Selection Draw, is now open for applications. This is the first time fans can apply for single-match tickets based on the ...
Advanced fraud detection system using machine learning to identify fraudulent transactions and activities. This project implements multiple machine learning algorithms including Random Forest, XGBoost ...
Background: Neovascular glaucoma (NVG) is one of the most severe complications of proliferative diabetic retinopathy (PDR), carrying a high risk of blindness. Establishing an effective risk prediction ...
ABSTRACT: Similarity-based prediction modeling is a common method for estimating the remaining useful life (RUL) of a machine. The present study proposes a novel similarity-based multidimensional ...
ABSTRACT: Road traffic accidents are one of the global safety and socioeconomic challenges. According to WHO (2024), it has caused over 1.19 million annual fatalities. It is also projected to cause ...
Abstract: To improve the problems such as low relevance, redundant features and the low accuracy of traditional fault diagnosis methods, a transformer fault diagnosis method based on the random forest ...
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