Revisiting Generative Adversarial Networks for Binary Semantic Segmentation on Imbalanced Datasets

Anomalous pavement surface conditions detection aims to detect pixels representing anomalous states, such as cracks, on pavement surface images automatically by algorithms. Recently, deep learning models have been intensively applied to related topics with outstanding performance. However, most existing deep learning-related solutions rarely achieve a stable performance on diverse datasets. To address this issue, in this work, we propose a deep learning framework based on conditional Generative Adversarial Networks for anomalous region detection on pavement images at the pixel level. …

adversarial algorithms binary cs.cv cs.lg datasets deep learning detection diverse generative generative adversarial networks images networks performance pixels segmentation semantic solutions surface topics