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Dennis Sprute, Juhi Soni, Gesa Benndorf
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10.1109/tpami.2024.3369699 · doi-reference
From superpixels to foundational models: an overview of unsupervised and generalizable image segmentation
10.1016/j.cag.2024.104014 · doi-reference
A survey on deep learning-based semi-supervised semantic segmentation
10.1145/3806766 · doi-reference
Irregular facades: a dataset for semantic segmentation of the free facade of modern buildings
10.3390/buildings14092602 · doi-reference
Improving facade parsing with vision transformers and line integration
10.1016/j.aei.2024.102463 · doi-reference
A deep learning method for building façade parsing utilizing improved SOLOv2 instance segmentation
10.1016/j.enbuild.2023.113275 · doi-reference
Deep learning for detecting building façade elements from images considering prior knowledge
10.1016/j.autcon.2021.104016 · doi-reference
DeepFacade: a deep learning approach to facade parsing with symmetric loss
10.1109/tmm.2020.2971431 · doi-reference
ATLAS: a three-layered approach to facade parsing
10.1007/s11263-015-0868-z · doi-reference
A review on artificial intelligence applications for facades
10.1016/j.buildenv.2024.112310 · doi-reference
Deep learning and remote sensing for scalable building age prediction in urban energy modeling
10.1016/j.enbuild.2025.116303 · doi-reference
Towards an automated image-based estimation of building age as input for building energy modeling (BEM)
10.1016/j.enbuild.2023.113166 · doi-reference
A method for using street view imagery to auto-extract window-to-wall ratios and its relevance for urban-level daylighting and energy simulations
10.1016/j.buildenv.2021.108108 · doi-reference
DeepWindows: windows instance segmentation through an improved mask R-CNN using spatial attention and relation modules
10.3390/ijgi11030162 · doi-reference
Enhancing building performance evaluation through Google street view: a multimodal transfer learning framework
10.1016/j.enbuild.2025.115968 · doi-reference
Extracting principal building variables from automatically collected urban scale façade images for energy conservation through deep transfer learning
10.1016/j.apenergy.2023.121228 · doi-reference
AI-powered automated building façade segmentation and BIPV system potential prediction using CycleGAN and PVGIS
10.1016/j.enbuild.2026.117020 · doi-reference
Learning from other cities: transfer learning based multimodal residential energy prediction for cities with limited existing data
10.1016/j.enbuild.2025.115723 · doi-reference
Prediction and analysis of heating energy demand for detached houses by computer vision
10.1016/j.enbuild.2019.03.036 · doi-reference
Mapping facade materials utilizing zero-shot segmentation for applications in urban microclimate research
10.1038/s41598-025-86307-1 · doi-reference
UAV-BIM-BEM: an automatic unmanned aerial vehicles-based building energy model generation platform
10.1016/j.enbuild.2024.115120 · doi-reference
Framework for a UAS-based assessment of energy performance of buildings
10.1016/j.enbuild.2021.111266 · doi-reference
Understanding building energy efficiency with administrative and emerging urban big data by deep learning in glasgow
10.1016/j.enbuild.2022.112331 · doi-reference
Residential building facade segmentation in the urban environment
10.1016/j.buildenv.2021.107921 · doi-reference
Using machine learning to enrich building databases—methods for tailored energy retrofits
10.3390/en13102574 · doi-reference
Automatic window detection in facade images
10.1016/j.autcon.2018.10.007 · doi-reference
A review of internal and external influencing factors on energy efficiency design of buildings
10.1016/j.enbuild.2020.109944 · doi-reference
Building information modelling based building energy modelling: a review
10.1016/j.apenergy.2019.01.032 · doi-reference