Semantic segmentation in 3D meshes is the classification of its constituent element (s) into
specific classes or categories. Using the powerful feature extraction abilities of deep neural …

Textured meshes are becoming an increasingly popular representation combining the 3D
geometry and radiometry of real scenes. However, semantic segmentation algorithms for …

A textured urban 3D mesh is an important part of 3D real scene technology. Semantically
segmenting an urban 3D mesh is a key task in the photogrammetry and remote sensing …

The photogrammetric 3-D textured mesh model (TMM) obtained by unmanned aerial vehicle
provides accurate geometric shapes and realistic textures. The 3-D semantics derived from …

Utilizing 3D mesh data presents myriad advantages for representing actual environments,
encompassing the capability to exhibit geometric information and high-quality textures …

The need for faster, flexible, efficient, and more autonomous production methods created the
concept of Industry 4.0, which contains the idea of simultaneously managing the physical …

The task of semantic segmentation is currently a very interesting subject in the
geoinformatics domain. Semantic segmentation enables the automatic classification of data …

Over the past years, geospatial data acquisition has become more redundant, more
complete, faster, and denser–both spatially and temporally. Sensors such as cameras and …