Browsing by Subject "Machine learning"
Now showing items 1-5 of 5
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Advanced parametrization of graphomotor difficulties in school-aged children
(IEEE Acces. 2020 Jun 17;8:112883-112897, 2020-06-17)School-aged children spend 31–60% of their time at school performing handwriting, which is a complex perceptual-motor skill composed of a coordinated combination of fine graphomotor movements. As up to ... -
Comparison of CNN-learned vs. handcrafted features for detection of Parkinson's disease dysgraphia in a multilingual dataset
(Frontiers in Neuroinformatics. 2022;(16):877139, 2022)Parkinson’s disease dysgraphia (PDYS), one of the earliest signs of Parkinson’s disease (PD), has been researched as a promising biomarker of PD and as the target of a noninvasive and inexpensive ... -
Computer-aided diagnosis of graphomotor difficulties utilizing direction-based fractional order derivatives
(Cognitive Computation. 2024 Nov;17(13), 2024-11)Children who do not sufficiently develop graphomotor skills essential for handwriting often develop graphomotor disabilities (GD), impacting the self-esteem and academic performance of the individual. ... -
Improving resilience of sensors in planetary exploration using data-driven models
(Machine Learning: Science and Technology. 2023 Set 4;4:035041, 2023-09-04)Improving the resilience of sensor systems in space exploration is a key objective since the environmental conditions to which they are exposed are very harsh. For example, it is known that the presence ...