ISBN: 9783725863501 - machine learning for pattern recognition (2nd edition) (9 risultati)

Condizione: New.

HRD. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

HRD. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Condizione: New. Print on Demand.

Condizione: New. Print on Demand.

Condizione: New. PRINT ON DEMAND.

Hardcover. Condizione: new. Hardcover. In the recent digital age, machine learning technology has made 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 has many challenges and problems. This 2nd edition 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 studies in each paper not only showcase the latest advancements in machine learning algorithms but also discuss their successful applications and the challenges encountered in real-world scenarios.As Guest Editors, we are honored to present this 2nd edition Reprint, and we hope that readers, whether researchers, engineers, or 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. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Buch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In the recent digital age, machine learning technology has made 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 has many challenges and problems. This 2nd edition 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 studies in each paper not only showcase the latest advancements in machine learning algorithms but also discuss their successful applications and the challenges encountered in real-world scenarios.As Guest Editors, we are honored to present this 2nd edition Reprint, and we hope that readers, whether researchers, engineers, or 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.…

Buch. Condizione: Neu. Machine Learning for Pattern Recognition (2nd Edition) | Buch | Englisch | 2026 | MDPI AG | EAN 9783725863501 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.