{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/a-hyperspectral-and-rgb-dataset-for-building","title":"A Hyperspectral and RGB Dataset for Building Facade Segmentation","arxiv_id":"2212.02749","date":"2022-12-06","proceeding":null,"authors":["Nariman Habili","Ernest Kwan","Weihao Li","Christfried Webers","Jeremy Oorloff","Mohammad Ali Armin","Lars Petersson"],"abstract":"Hyperspectral Imaging (HSI) provides detailed spectral information and has been utilised in many real-world applications. This work introduces an HSI dataset of building facades in a light industry environment with the aim of classifying different building materials in a scene. The dataset is called the Light Industrial Building HSI (LIB-HSI) dataset. This dataset consists of nine categories and 44 classes. In this study, we investigated deep learning based semantic segmentation algorithms on RGB and hyperspectral images to classify various building materials, such as timber, brick and concrete.","url_abs":"https://arxiv.org/abs/2212.02749v1","url_pdf":"https://arxiv.org/pdf/2212.02749v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[],"tasks":[{"task_slug":"semantic-segmentation","task_name":"Semantic Segmentation"}],"methods":[],"datasets_introduced":[{"slug":"lib-hsi","name":"LIB-HSI","full_name":"RGB and Hyperspectral images of Building Facades"}],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/2212.02749","atlas_url":"https://app.syntology.ai/?focus=2212.02749","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}