UID:
almahu_9950024218902882
Umfang:
IX, 250 p. 73 illus., 64 illus. in color.
,
online resource.
Ausgabe:
1st ed. 2025.
ISBN:
9783031948022
Serie:
Lecture Notes in Networks and Systems, 1466
Inhalt:
This book offers innovative insights into the integration of machine learning and inverse problems, showcasing cutting-edge methodologies that enhance computational efficiency and accuracy. By leveraging artificial intelligence, optimization techniques, and high-performance computing, it addresses complex challenges across various scientific and industrial domains. The contributions featured in this book encompass theoretical advancements and practical applications, highlighting diverse topics such as data-driven approaches, uncertainty quantification, and algorithmic innovations. This interdisciplinary collection is designed for researchers, practitioners, and students interested in the transformative potential of informatics and computational sciences. By presenting meticulously reviewed papers from the Third International Conference on Mathematical and Computational Sciences (ICMDS 2024), this issue serves as a valuable resource for fostering further research and development, inspiring new approaches to solving pressing problems through advanced computational methods.
Anmerkung:
HMM-GMM Acoustic Modeling for Arabic Speech Recognition System -- Machine Learning Prediction of Long Jump Performance Based on Biomechanical Factors -- Arabic Sign Language Classification using CNN-LSTM Integration for Enhanced Gesture Recognition -- Data Exploration by Unifying Clustering and Association Rule mining.
In:
Springer Nature eBook
Weitere Ausg.:
Printed edition: ISBN 9783031948015
Weitere Ausg.:
Printed edition: ISBN 9783031948039
Sprache:
Englisch
DOI:
10.1007/978-3-031-94802-2
URL:
https://doi.org/10.1007/978-3-031-94802-2
URL:
Volltext
(URL des Erstveröffentlichers)
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