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경량 딥러닝을 이용한 다중 손상 자동탐지를 위한 객체 증강
딘윈넉현 ( Dinh Nguyen-ngoc-han ),안용한 ( Ahn Yong-han ) 한국구조물진단유지관리공학회 2022 한국구조물진단유지관리공학회 학술발표대회 논문집 Vol.26 No.1
Computer Vision (CV) -based construction damages has been widely developed and resulted in potential alternative over traditional visual inspection. Howerver, the current deep learning models require an enormous data size, and relatively computational-expensive. Therefore, collecting and create more data has been an crucial state in the process of excecution, especially in the context of multi-damages detection with surround different types of object images. Therefore, an object aumentation and lightweight neural network has been introduced with the aim to improve the computional perfomance and address limitation of shortage and imbalance data