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Unsupervised crack detection on complex stone masonry surfaces
Towards this direction, some of the most popular state of the art CNN (Convolutional Neural Network) architectures are deployed and modified to binary classify the images or image patches by predicting a specific class for the tested imagery; 'Crack' or 'No crack', and detect and localize those cracks on the RGB imagery with high accuracy.
Seafloor-Invariant Caustics Removal from Underwater Imagery
Mapping the seafloor with underwater imaging cameras is of significant importance for various applications including marine engineering, geology, geomorphology, archaeology and biology.
Image-based underwater 3D reconstruction for Cultural Heritage: from image collection to 3D. Critical steps and considerations
Underwater Cultural Heritage (CH) sites are widely spread; from ruins in coastlines up to shipwrecks in deep.
Shallow Water Bathymetry Mapping from UAV Imagery based on Machine Learning
The determination of accurate bathymetric information is a key element for near offshore activities, hydrological studies such as coastal engineering applications, sedimentary processes, hydrographic surveying as well as archaeological mapping and biological research.
