SEMANTIC SEGMENTATION OF BURNED AREAS IN SATELLITE IMAGES USING A U-NET-BASED CONVOLUTIONAL NEURAL NETWORK

21 citations as recorded by crossref.

1. BA_EnCaps: Dense Capsule Architecture for Thermal Scrutiny Q. Safder et al.
2. Supervised Machine Learning Approaches on Multispectral Remote Sensing Data for a Combined Detection of Fire and Burned Area J. Florath & S. Keller
3. Forest Burned Area Detection Using a Novel Spectral Index Based on Multi-Objective Optimization B. Wu et al.
4. Burned Area Detection in the Eastern Canadian Boreal Forest Using a Multi-Layer Perceptron and MODIS-Derived Features H. Meimand et al.
5. TranSegNet: A Hybrid Transformer Model for Satellite Imagery Segmentation with Performance Benchmark Against U-Net Variants R. Ingole et al.
6. A repeatable change detection approach to map extreme storm-related damages caused by intense surface runoff based on optical and SAR remote sensing: Evidence from three case studies in the South of France A. Cerbelaud et al.
7. National Disaster Management and Monitoring Using Satellite Remote Sensing and Geo-Information J. Park et al.
8. SSU-Net: A Model for Mapping Burned Areas Using Landsat-8 and Sentinel-2 S. Cui et al.
9. Correlation Between Visible Landscape Elements and Locals’ Spatial Preference in Historical District Public Open Spaces via VR-Based EEG Measurement: A Case Study of Quanzhou Z. Zhang et al.
10. Burnt-Net: Wildfire burned area mapping with single post-fire Sentinel-2 data and deep learning morphological neural network S. Seydi et al.
11. Magnifier: A Multigrained Neural Network-Based Architecture for Burned Area Delineation D. Cambrin et al.
12. Semantic Segmentation of Satellite Images using 2 various U-Net Architectures: A Comparison Study N. Gonthina & . L.V. Narasimha Prasad
13. Unification of Semantic and Instance Segmentation with BoundaryX T. Boyadzhiev & K. Ivanova
14. Burned Area Mapping Using Unitemporal PlanetScope Imagery With a Deep Learning Based Approach A. Cho et al.
15. A Quadratic Morphological Deep Neural Network Fusing Radar and Optical Data for the Mapping of Burned Areas S. Seydi et al.
16. BASNet: Burned Area Segmentation Network for Real-Time Detection of Damage Maps in Remote Sensing Images W. Bo et al.
17. Mapping Pluvial Flood-Induced Damages with Multi-Sensor Optical Remote Sensing: A Transferable Approach A. Cerbelaud et al.
18. U-Net-STN: A Novel End-to-End Lake Boundary Prediction Model L. Yin et al.
19. A Method for Mapping and Associating Burned Areas with Agricultural Practices Within the Brazilian Cerrado P. Castro Abreu et al.
20. Deep Learning Approaches for Wildland Fires Using Satellite Remote Sensing Data: Detection, Mapping, and Prediction R. Ghali & M. Akhloufi
21. FBA-DPAttResU-Net: Forest burned area detection using a novel end-to-end dual-path attention residual-based U-Net from post-fire Sentinel-1 and Sentinel-2 images E. Khankeshizadeh et al.