SEMANTIC SEGMENTATION OF FOREST STANDS OF PURE SPECIES AS A GLOBAL OPTIMIZATION PROBLEM

10 citations as recorded by crossref.

1. A review of deep learning methods for semantic segmentation of remote sensing imagery X. Yuan et al. 10.1016/j.eswa.2020.114417
2. Deep Learning Spatial-Spectral Classification of Remote Sensing Images by Applying Morphology-Based Differential Extinction Profile (DEP) N. Kakhani et al. 10.3390/electronics10232893
3. Ticino: A multi-modal remote sensing dataset for semantic segmentation M. Barbato et al. 10.1016/j.eswa.2024.123600
4. Classification of tree species and stock volume estimation in ground forest images using Deep Learning J. Liu et al. 10.1016/j.compag.2019.105012
5. Sensing and Artificial Perception for Robots in Precision Forestry: A Survey J. Ferreira et al. 10.3390/robotics12050139
6. Semantic Segmentation of Multispectral Images via Linear Compression of Bands: An Experiment Using RIT-18 Y. Cai et al. 10.3390/rs14112673
7. Semantic segmentation of agricultural images: A survey Z. Luo et al. 10.1016/j.inpa.2023.02.001
8. Globe230k: A Benchmark Dense-Pixel Annotation Dataset for Global Land Cover Mapping Q. Shi et al. 10.34133/remotesensing.0078
9. FSUNet: lightweight full-scale information fusion UNet for seed coat thickness measurement Z. Zhang et al. 10.1080/23311932.2024.2424928
10. Method and Spatiotemporal Analysis for Impervious Surface Extraction Based on an Improved DeepLabV3+ Model X. Wang et al. 10.1109/JSTARS.2024.3511625