Regular inspections of sewer systems and pipelines are crucial for maintaining functionality. Since many structures are not directly accessible, a robotic platform equipped with a camera ring and laser scanner is employed. This paper presents a novel hybrid image stitching pipeline with a geometry-driven decision process that combines model-based and simplified geometric approaches to generate unwrapped pipe textures from homo...

Geospatial machine learning models are widely used in domains such as urban planning, public health, and transportation. However, understanding these models is challenging due to their inherent complexity. Traditional explainable artificial intelligence methods provide either global explanations that allow broad insights into the model, or detailed local explanations for individual predictions. This study builds on an establis...

3D deep-learning based models have been proposed to assist in the digitalization process of as-is infrastructure. Despite their outstanding performance to process large amounts of data, research on interpreting their execution rather than improving their outcome has been scarce. To further characterize the execution of these models, in this study we seek to identify influential parts of the input that contribute the most to a...

Deep learning methods such as Mask R‑CNN enable the precise delineation of single-tree crowns from remote sensing data. However, their segmentation performance still depends on local stand conditions. Using UAV multispectral imagery and lidar canopy height models (CHM), we assessed the influence of tree species composition, stand density, and foliage condition on the robustness of deep-learning-based single-tree segmentation....

Multiple viewpoint 3D reconstruction has been used in recent years to create accurate complete scenes and objects used for various applications. This is to overcome limitations of single viewpoint 3D digital imaging such as occlusion within the scene during the reconstruction process. In this paper, we propose a weighted point cloud fusion process using both local and global spatial information of the point clouds to fuse them...