A fine-tuned VGG-16 network with class activation mapping classifies and localizes mould, stain, and paint deterioration in building photos with 87.5% test accuracy.
In Multidisciplinary DigitalPublishing Institute: 2017
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Deep Learning for Detecting Building Defects Using Convolutional Neural Networks
A fine-tuned VGG-16 network with class activation mapping classifies and localizes mould, stain, and paint deterioration in building photos with 87.5% test accuracy.