With recent advances in non-contact sensing technology such as cameras, unmanned aerial
and ground vehicles, the structural health monitoring (SHM) community has witnessed a …

Data-driven methods in structural health monitoring (SHM) is gaining popularity due to
recent technological advancements in sensors, as well as high-speed internet and cloud …

The comprehensive intelligent development of the manufacturing industry puts forward new
requirements for the quality inspection of industrial products. This paper summarizes the …

With the advancement of machine learning (ML) and deep learning (DL), there is a great
opportunity to enhance the development of automatic crack detection algorithms. In this …

This paper compares the performance of common edge detectors and deep convolutional
neural networks (DCNN) for image-based crack detection in concrete structures. A dataset of …

The application of deep architectures inspired by the fields of artificial intelligence and
computer vision has made a significant impact on the task of crack detection. As the number …

SDNET2018 is an annotated image dataset for training, validation, and benchmarking of
artificial intelligence based crack detection algorithms for concrete. SDNET2018 contains …

Structural disaster damage detection and characterization is one of the oldest remote
sensing challenges, and the utility of virtually every type of active and passive sensor …

This research proposes an approach for vision-based autonomous navigation planning of
unmanned aerial vehicles for the collection of images suitable for the rapid post-earthquake …

The exponential growth of a multitude of cardiovascular diseases, leading to life frightening
conditions, makes fast and accurate computer-aided techniques that are relevant and …