The encoder consists of convolutional layers of the residual network for extracting crack features, and the decoder consists of deconvolutional layers for localizing the cracks in an input image. Thus, we propose a pixel‐level detection method for identifying road cracks in black‐box images using a deep convolutional encoder–decoder network. However, the cracks in these images are difficult to detect, because the images containing them often include objects other than roads. Black‐box cameras, which are becoming increasingly widespread at an affordable price, can be used as efficient road‐image collectors over a wide area. Accurate information concerning crack location and severity enables proactive management of the infrastructure. Timely monitoring of pavement cracks is essential for successful maintenance of road infrastructure.
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