BUILDING FOOTPRINT EXTRACTION FROM SPACE-BORNE IMAGERY USING DEEP NEURAL NETWORKS

11 citations as recorded by crossref.

1. Traditional Village Building Extraction Based on Improved Mask R-CNN: A Case Study of Beijing, China W. Wang et al.
2. Optimizing Land Use/Land Cover Mapping Accuracy: A Comprehensive Analysis of Random Forest with Explainable Artificial Intelligence Based Feature Importance Analysis M. Rihan et al.
3. Uzaktan Algılama Görüntülerinden Bina Çıkarımında FPN-ResNeXt50 ve VGG16-UNet Modellerinin Karşılaştırılması S. Şenses & E. Tanır Kayıkçı
4. SDSNet: Building Extraction in High-Resolution Remote Sensing Images Using a Deep Convolutional Network with Cross-Layer Feature Information Interaction Filtering X. Wang et al.
5. Recurrent Residual Deformable Conv Unit and Multi-Head with Channel Self-Attention Based on U-Net for Building Extraction from Remote Sensing Images W. Yu et al.
6. Building Extraction for Urban Infrastructure Mapping Using Deep Neural Networks and High-Resolution Remote Sensing Data S. Sharma et al.
7. Enhanced Hybrid U-Net Framework for Sophisticated Building Automation Extraction Utilizing Decay Matrix T. Wang et al.
8. ESSegNeXt: A Novel Building Extraction Framework Based on Generalized SamGeo and SegNeXt Models Using High-Resolution Remote Sensing Images Q. Lu et al.
9. A Deep Learning Approach for Automated Building Footprint Extraction from Cartosat Imagery K. Deka et al.
10. An interactive method for bridging the gap between deep learning based building contour segmentation and manual annotation Y. Tian et al.
11. Building Footprint Extraction for Large-Scale Basemaps Using Very-High-Resolution Satellite Imagery Y. Hakim & F. Tsai