首页|MiniCrack: A simple but efficient convolutional neural network for pixel-level narrow crack detection
MiniCrack: A simple but efficient convolutional neural network for pixel-level narrow crack detection
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NSTL
Elsevier
With the advancement of deep learning, the newly proposed neural networks are growing increasingly complicated to achieve great performance. In this context, we propose a simple but effective neural network called MiniCrack for narrow crack detection. We also propose a lightweight version, MiniCrack-Light, to adapt to scenarios with limited computing resources. MiniCrack and MiniCrack-Light outperform the current state-of-the-art neural networks on all three challenging testing data sets with fewer parameters and achieving stronger robustness. PixelShuffle and PixelUnshuffle designed for image super-resolution are successfully used to the field of image segmentation, which effectively alleviates the problems caused by pooling.
NSTL
Elsevier
