Proceedings of the Third ICMDS'24: Machine Learning, Inverse Problems and Related Fields

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Geliefert zwischen Di., 30.12.2025 und Mi., 31.12.2025

Details

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.


Features high-quality research papers presented at the International Conference on Mathematics Data Science ICMDS24 Focuses on the latest advancements in computational intelligence, machine learning, inverse problems, and related fields Highlights the intersection of theoretical research and practical applications, showcasing innovative solutions

Inhalt

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.

Weitere Informationen

  • Allgemeine Informationen
    • GTIN 09783031948015
    • Genre Technology Encyclopedias
    • Editor Amine Laghrib, Abdelghani Ghazdali
    • Lesemotiv Verstehen
    • Anzahl Seiten 250
    • Herausgeber Springer Nature Switzerland
    • Größe H235mm x B155mm
    • Jahr 2025
    • EAN 9783031948015
    • Format Kartonierter Einband
    • ISBN 978-3-031-94801-5
    • Veröffentlichung 12.06.2025
    • Titel Proceedings of the Third ICMDS'24: Machine Learning, Inverse Problems and Related Fields
    • Untertitel Lecture Notes in Networks and Systems 1466
    • Sprache Englisch

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