Edge detection is one of the most important and fundamental problems in the field of
computer vision and image processing. Edge contours extracted from images are widely …

Machine vision, an interdisciplinary field that aims to replicate human visual perception in
computers, has experienced rapid progress and significant contributions. This paper traces …

Computer vision-based crack analysis for civil infrastructure has become popular to
automatically process inspection imaging data for crack detection, localisation and …

This paper proposes a Deep Learning based edge detector, which is inspired on both HED
(Holistically-Nested Edge Detection) and Xception networks. The proposed approach …

Coastlines are important basic geographic elements and map** their spatial and attribute
changes can help monitor, model and manage coastal zones. Traditional studies focused on …

Deep learning‐based structural damage detection methods overcome the limitation of
inferior adaptability caused by extensively varying real‐world situations (eg, lighting and …

A number of image processing techniques (IPTs) have been implemented for detecting civil
infrastructure defects to partially replace human‐conducted onsite inspections. These IPTs …

Edge detection is the basis of many computer vision applications. State of the art
predominantly relies on deep learning with two decisive factors: dataset content and network …

Edge detection is a critical component of many vision systems, including object detectors
and image segmentation algorithms. Patches of edges exhibit well-known forms of local …

Edge detection technology aims to identify and extract the boundary information of image
pixel mutation, which is a research hotspot in the field of computer vision. This technology …