Image/video based defect recognition is a crucial task in automating visual inspection of
concrete structures. Although some progress has been made to automatically recognize
defects in concrete structural images, significant challenges still exist. In this work, we
propose a deep convolutional neural network architecture that embeds novel spatial-
channel interaction based concurrent attention (SCA) for multi-target, multi-class defect
recognition. SCA module stems from novel kernel salient feature (KSF) encoder that …