Deep learning for crack-like object detection

Zhang, Kaige; Cheng, Heng-Da

ISBN 10: 1032181192 / ISBN 13: 9781032181196

Verlag: CRC Press, 2024

Beschreibung

pages cm First edition "A Science Publishers book. Includes bibliographical references and index.

Bestandsnummer des Verkäufers 26397566879

Bibliografische Details

• Titel: Deep learning for crack-like object detection
• Verlag: CRC Press
• Erscheinungsjahr: 2024
• Sprache: Englisch
• ISBN-10: 1032181192
• ISBN-13: 9781032181196
• Einband: Softcover
• Zustand: New

Über diesen Titel

Inhaltsangabe

Accurately detecting crack localization is not an easy task. This book addresses important issues in detecting crack-like objects and provides a practical smart pavement surface inspection system using deep learning.

Über die Autorin bzw. den Autor

Kaige Zhang has a B.S. degree (2011) in electronic engineering from the Harbin Institute of Technology, China, and a Ph.D. degree (2019) in computer science from Utah State University, USA. His research interests include computer vision, machine learning, and the applications on intelligent transportation systems, precision agriculture, and biomedical data analytics. Dr. Zhang has been the reviewer for many top journals in his research areas, such as IEEE Transactions on ITS, IEEE Trans. On T-IV, J. of Comput. in Civil Eng., Scientific Report, etc.

Heng-Da Cheng has a Ph.D. in Electrical Engineering from Purdue University, West Lafayette, IN, USA in 1985 under the supervision Prof. K. S. Fu. He is a Full Professor with the Department of Computer Science, Utah State University, Logan, UT. He has authored over 350 technical papers and is the Associate Editor of Pattern Recognition, Information Sciences, and New Mathematics and Natural Computation.