SOURCE-LINKED INTELLIGENCE

Forensic Analysis of Concrete Through Image Processing

CORDIS · observation · Publication date unknown

haracterizing, and quantifying various concrete defects such as cracks, spalling, corrosion, and delamination, the project aims to extract intricate patterns and features from concrete images through deep learning, improving FA accuracy. This ambitious objective pushes the boundaries of current research in FA of concrete, opening the door to discoveries and advancements. By combining IP and CNN for FACIP, the research aims to develop innovative methodologies and tools that surpass the limitations of existing techniques, such as Core Cutting, Schmidt Hammer, and UPVs, providing accurate and reliable analysis results. This contributes to developing more effective concrete maintenance, repair, and structural integrity assessment strategies. Ultimately, the project aims to provide concrete forensic experts with advanced, reliable, and time-efficient analysis methods, enhancing concrete forensic investigations' overall accuracy and effectiveness. Forensic Analysis of Concrete, Image Processing, Convolutional Neural Networks, Compressive strength

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recordType

award

status

SIGNED

region

EU

value

226751.04

unit

EUR