DenseSPH-YOLOv5: An automated damage detection model based on DenseNet and Swin-Transformer prediction head-enabled YOLOv5 with attention mechanism

Arunabha M. Roy; Jayabrata Bhaduri

doi:10.1016/j.aei.2023.102007

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DenseSPH-YOLOv5: An automated damage detection model based on DenseNet and Swin-Transformer prediction head-enabled YOLOv5 with attention mechanism

Arunabha M. Roy Jayabrata Bhaduri

Year: 2023 Journal: Advanced Engineering Informatics Vol: 56 Pages: 102007-102007 Publisher: Elsevier BV

DOI: 10.1016/j.aei.2023.102007

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Keywords:

Computer science Artificial intelligence Object detection Minimum bounding box Feature extraction Block (permutation group theory) Deep learning Pattern recognition (psychology) Machine learning Data mining

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Topics

Infrastructure Maintenance and Monitoring

Physical Sciences → Engineering → Civil and Structural Engineering

Non-Destructive Testing Techniques

Physical Sciences → Engineering → Mechanical Engineering

Geophysical Methods and Applications

Physical Sciences → Engineering → Ocean Engineering

DenseSPH-YOLOv5: An automated damage detection model based on DenseNet and Swin-Transformer prediction head-enabled YOLOv5 with attention mechanism

Metrics

Citation History

Topics

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