Machine learning (ML) has emerged as a powerful tool to analyze gait data, yet the “black-box” nature of many ML models hinders their clinical application. Explainable artificial intelligence (XAI) ...
Abstract: Semantic communication for classification as the intended task at the receiver involves encoding the message signal to maximize the classifier’s performance in terms of accuracy at the ...
Nope, streaming hasn’t slowed its relentless takeover of the TV viewing universe. According to a recently released Nielsen report, streaming viewing surpassed linear TV (broadcasting and cable) for ...
ABSTRACT: The stochastic configuration network (SCN) is an incremental neural network with fast convergence, efficient learning and strong generalization ability, and is widely used in fields such as ...
Motor imagery (MI) in combination with neurofeedback (NF) has emerged as a promising approach in motor neurorehabilitation, facilitating brain activity modulation and promoting motor learning.
Abstract: Linear discriminant analysis (LDA) faces challenges in practical applications due to the small sample size (SSS) problem and high computational costs. Various solutions have been proposed to ...
This repository houses the files related to my homework assignments for the Multivariate Analysis class. Throughout the coursework, I utilized R Studio for all of my work. In addition to the homework, ...
In this paper, a new method for supervised classification of hyperspectral images is proposed for the case in which the size of the training sample is small. It consists of replacing in the ...
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