A toolbox for biosignal processing written in Python. The toolbox bundles together various signal processing and pattern recognition methods geared towards the analysis of biosignals. The code below ...

In the pre-large language model (LLM) Stack Overflow era, the challenge was discerning which code snippets to adopt and adapt effectively. Now, while generating code has become trivially easy, the ...

Abstract: Sign language recognition (SLR) involves translating visual gestures into meaningful text or speech, bridging the communication gap between signers and non-signers. However, real-time ...

Abstract: Artificial Intelligence (AI) is a pivotal technology with diverse applications in fields such as algorithm design, robotic automation, image processing, and machine learning. This paper ...

Manhole cover defect recognition is of significant practical importance as it can accurately identify damaged or missing covers, enabling timely replacement and maintenance. Traditional manhole cover ...

In this study, we aimed to apply laboratory blood analysis to identify the hematological (based on hemoglobin concentration, erythrocytes, hematocrit, and RDW count) profiles associated with the most ...

Intracranial stereoelectroencephalography (SEEG) is broadly used in the presurgical evaluation of intractable epilepsy, due to its high temporal resolution in neural activity recording and high ...

Automated interpretation of echocardiography by deep neural networks could support clinical reporting and improve efficiency. Whereas previous studies have evaluated spatial relationships using still ...

pyVSR is a Python toolkit aimed at running Visual Speech Recognition (VSR) experiments in a traditional framework (e.g. handcrafted visual features, Hidden Markov Models for pattern recognition). The ...