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發(fā)表于 2025-3-21 16:21:35 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Graphonomics in Human Body Movement. Bridging Research and Practice from Motor Control to Handwriting Analysis and Recognition
編輯Antonio Parziale,Moises Diaz,Filipe Melo
視頻videohttp://file.papertrans.cn/389/388152/388152.mp4
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: ;
出版日期Conference proceedings 2023
版次1
doihttps://doi.org/10.1007/978-3-031-45461-5
isbn_softcover978-3-031-45460-8
isbn_ebook978-3-031-45461-5Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
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沙發(fā)
發(fā)表于 2025-3-21 21:06:56 | 只看該作者
On the Analysis of Saturated Pressure to Detect Fatiguenature, under different levels of fatigue. Experimental results demonstrate a significant rise in the proportion of saturated samples following strenuous exercise in tasks performed without resting wrist. The analysis of saturation highlights significant differences when comparing the results to the baseline situation and strenuous fatigue.
板凳
發(fā)表于 2025-3-22 02:44:32 | 只看該作者
Graphonomics in Human Body Movement. Bridging Research and Practice from Motor Control to Handwriting Analysis and Recognition978-3-031-45461-5Series ISSN 0302-9743 Series E-ISSN 1611-3349
地板
發(fā)表于 2025-3-22 08:04:44 | 只看該作者
A Short Review on Graphonometric Evaluation Tools in Childrenetric evaluation as a means to detect possible difficulties or disorders in learning to write. The article concludes by highlighting the need to agree on an evaluation methodology and to combine databases.
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發(fā)表于 2025-3-22 10:54:55 | 只看該作者
Assessment of?Developmental Dysgraphia Utilising a?Display Tablet(HPSQ–C). Using machine learning models based on a gradient-boosting algorithm, we were able to support the DD diagnosis with up to 83.6% accuracy. The HPSQ–C total score was estimated with a minimum error equal to 10.34%. Children with DD spent significantly higher time in-air, they had a higher nu
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發(fā)表于 2025-3-22 14:31:48 | 只看該作者
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發(fā)表于 2025-3-22 20:12:20 | 只看該作者
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發(fā)表于 2025-3-23 00:16:06 | 只看該作者
Feature Evaluation in?Handwriting Analysis for?Alzheimer’s Disease Using Bayesian Networks among the most effective features for predicting impairment symptoms through handwriting analysis and deepen our understanding of the underlying cognitive functions affected. The results showed that the Bayesian Network chooses features conditionally dependent on the determination of the disease,
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發(fā)表于 2025-3-23 03:18:26 | 只看該作者
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發(fā)表于 2025-3-23 08:48:18 | 只看該作者
Estimating the?Optimal Training Set Size of?Keyword Spotting for?Historical Handwritten Document Traa benchmark for performance evaluation show that a training set made of 5 to 8 pages is enough for achieving the largest reduction, independently of the actual pages included in the training set and the corresponding keyword lists. They also show that the actual time reduction depends much more on t
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