SEMANTIC SEGMENTATION OF UAV IMAGES BASED ON U-NET IN URBAN AREA

7 citations as recorded by crossref.

1. UAVs-Based Visual Localization via Attention-Driven Image Registration Across Varying Texture Levels Y. Ren et al. https://doi.org/10.3390/drones8120739
2. ІНТЕЛЕКТУАЛЬНА СИСТЕМА АВТОНОМНОЇ НАВІГАЦІЇ БПЛА НА ОСНОВІ СЕМАНТИЧНОГО АНАЛІЗУ ЗОБРАЖЕНЬ І. Савчук & Т. Кадильникова https://doi.org/10.15421/452535
3. Enhancing UAS-Based Multispectral Semantic Segmentation Through Feature Engineering E. Vollmer et al. https://doi.org/10.1109/JSTARS.2025.3537330
4. Assessment of vegetation indices for mapping burned areas using a deep learning method and a comprehensive forest fire dataset from Landsat collection G. Suárez-Fernández et al. https://doi.org/10.1016/j.asr.2024.12.001
5. Utilizing UAV for the Detection of Vacant Urban Spaces: Implications for Sustainable Infill Development A. Shojaeean https://doi.org/10.48123/rsgis.1592089
6. Assessment of building extraction and geometric corrections from UAV image using Mask R-CNN deep neural network algorithm E. Kaya https://doi.org/10.1080/22797254.2026.2618374
7. Semantic segmentation of oblique UAV video based on ConvLSTM in complex urban area A. Majidizadeh et al. https://doi.org/10.1007/s12145-024-01355-x