MACHINE LEARNING FOR CRACK DETECTION ON CONCRETE STRUCTURES BY VSS: APPLICATION OF MACHINE LEARNING FOR CRACK DETECTION ON CONCRETE STRUCTURES USING CONVOLUTIONAL NEURAL NETWORK ARCHITECT - Softcover

Swaroop, A.H.L; Saathvik, R. Noga; Dey, Subhashish

Softcover

ISBN 10: 6208451485 ISBN 13: 9786208451486

Publisher: LAP LAMBERT Academic Publishing, 2025

Synopsis

Concrete structures and the associated cracking represent a persistent challenge within the fields of construction and civil engineering, a dilemma that has persisted for decades. Generally, cracks arise from the expansion and contraction of materials, which can lead to various forms of damage within buildings. Engineers typically address these damages and irregularities through manual inspections or by employing predictive models developed using machine learning techniques, thereby facilitating a comprehensive assessment of the structural health of the edifices. This research aims to implement tools such as the VGG 16 network model alongside other machine learning methodologies to identifycracks in concrete structures. We propose a model that integrates Convolutional Neural Networks (CNN) with a VGG-based architecture. For image processing and segmentation, we have employed the gradient boosting algorithm. The datasets utilized in this study were sourced from the Kaggle platform, and the Hugging Face Transformers library was leveraged for implementation. To assess the performance of the developed models, metrics including precision, accuracy, recall, and F1 score were employed.

Edition details

• Publisher: LAP LAMBERT Academic Publishing
• Publication date: 2025
• Language: English
• ISBN 10: 6208451485
• ISBN 13: 9786208451486
• Binding: Paperback
• Number of pages: 88