Browsing by Author "Costa, Samuel Sampaio"
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- Real-time human activity recognition with KANsPublication . Costa, Samuel Sampaio; Pato, Matilde Pós-de-Mina; Datia, Nuno Miguel SoaresAbstract Kolmogorov-Arnold Networks (KANs) represent a breakthrough in deep learning by generalizing the Kolmogorov-Arnold Theorem (KAT) to networks of arbitrary depth and width. This theorem facilitates the decomposition of multivariate functions into constituent one-dimensional elements, with learnable activation functions on weights and the sum operator on nodes. KANs have been shown to exhibit robust performance in function approximation, validated across mathematical, physical, and practical domains such as traffic prediction and medical diagnostics. This study focuses on 3 objectives: (1) validating that KANs may be used in classification tasks applied to the real-world by comprehensive evaluations on OpenML, Kaggle and UCI datasets, (2) enhancing Human Activity Recognition (HAR) systems using KANs, and (3) applying these networks to Real-Time HAR in mobile devices. Tests were conducted to evaluate KANs with 7 different kernels. They demonstrate high classification performance compared to conventional machine learning approaches and MLP, and showcase reasonable latency for real-time HAR detection. These findings underscore KANs’ potential as scalable, interpretable tools in modern machine learning applications given their favorable neural scaling laws.