Machine Learning for Pattern Recognition

ISBN 10: 3725815917 / ISBN 13: 9783725815913

Published by MDPI AG, 2024

About this Item

Machine Learning for Pattern Recognition | Buch | Englisch | 2024 | MDPI AG | EAN 9783725815913 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.

Seller Inventory # 129794317

Bibliographic Details

• Title: Machine Learning for Pattern Recognition
• Publisher: MDPI AG
• Publication Date: 2024
• Language: English
• ISBN 10: 3725815917
• ISBN 13: 9783725815913
• Binding: Buch
• Condition: Neu
• Dimensions: 250W x 175H x 18D millimeters 250 millimeters width by 175 millimeters height by 18 millimeters depth
• Weight: 700 grams
• Seller catalogs:
  • Bücher

About this title

Synopsis

In recently arisen digital age, machine learning technology has made huge significant progress, revolutionizing applications in fields such as image recognition, speech processing, and natural language processing. These technologies have not only changed our daily lives, but have also had a profound impact on medicine, finance, transportation and other fields. However, pattern recognition, as an important branch of machine learning, still faces many challenges and problems. This reprint brings together contributions from leading experts in their fields. Each paper provides valuable insights into the latest trends, methods, and challenges in state-of-the-art applications of machine learning for pattern recognition. In addition, the research in each paper not only showcases the latest advancements in machine learning algorithms but also discusses their successful applications and the challenges encountered in real-world scenarios. As editors, we are honored to present this reprint, and we hope that readers, whether they be researchers, engineers, and students, will find inspiration and guidance in these papers as they explore the growing field of machine learning for pattern recognition. We express our gratitude to the authors for their outstanding contributions, to the reviewers for their critical evaluation, and to the assistant editor Mr. Musea Wu for his enthusiastic help. We are also sincerely grateful to our readers, whose curiosity and enthusiasm continue to drive innovation in this exciting field.