Apr 13, 2023 · In this paper, we propose Context Contrasted Net(CCN), which utilizes the common convolution and the dilated convolution to extract features of ...
To overcome the above challenges, we first construct Context Contrasted Network (CCN) to capture multi-scales features. By contrasting contextual features with ...
... pavement defect images, this study introduces CSNet, a pixel-level pavement crack detection model that integrates contextual features with attention mechanisms.
Missing: CCN: Contrasted
Oct 17, 2022 · CCN: Pavement Crack Detection with Context Contrasted Net. Neural Information Processing · Asphalt pavement crack detection based on multi-scale ...
Jun 18, 2024 · In this paper, the network proposed a fully automated crack detection and classification using deep convolution neural network (DCNN) ...
SwinCrack can produce more accurate and continuous descriptions of pavement cracks by modeling long-range interactions and adaptive spatial aggregation compared ...
Missing: CCN: Contrasted
Dec 10, 2020 · In this paper, a crack identification method based on a deep CNN fusion model is proposed. First, the image dataset is established, and the ...
Nov 25, 2020 · This method uses shape descriptors to distinguish between irregular texture and uneven brightness features, and finally uses SVM classifier to ...
Apr 19, 2024 · Abstract—Crack detection has become an indispensable, in- teresting yet challenging task in the computer vision commu-.
May 31, 2024 · PDF | Achieving high detection accuracy of pavement cracks with complex textures under different lighting conditions is still challenging.