mlsanityData to 7 Oct 2026

A Hyperspectral and RGB Dataset for Building Facade Segmentation

arXiv 2212.02749 ↗First posted 6 Dec 2022cs.CVcited by 7

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Abstract (arXiv)

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.

Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). Builds on 8 of its 23 references that are in the map. First posted on arXiv 6 Dec 2022.

Builds on

8 of 23 references.

References · 8

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2014Adam: A Method for Stochastic Optimizationcited by 36,960
  3. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,604
  4. 2014Fully Convolutional Networks for Semantic Segmentationcited by 4,845
  5. 2017Squeeze-and-Excitation Networkscited by 4,763
  6. 2019HybridSN: Exploring 3D-2D CNN Feature Hierarchy for Hyperspectral Image Classificationcited by 91
  7. 2021SpectralNET: Exploring Spatial-Spectral WaveletCNN for Hyperspectral Image Classificationcited by 12
  8. 2021Hyperspectral Image Segmentation based on Graph Processing over Multilayer Networkscited by 2

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 3; 2024: 2; 2025: 1; 2026: 1.

7 papers.