PERPUSTAKAAN BIG

1. Self-supervised monocular depth estimation from oblique UAV videos p. 1-14
2. Classifying rock slope materials in photogrammetric point clouds using robust color and geometric features p. 15-29
3. Radiative transfer modeling to measure fire impact and forest engineering resilience at short-term p. 30-41
4. Learning deep cross-scale feature propagation for indoor semantic segmentation p. 42-53
5. Juggling with representations: On the information transfer between imagery, point clouds, and meshes for multi-modal semantics p. 55-68
6. A two-step mapping of irrigated corn with multi-temporal MODIS and Landsat analysis ready data p. 69-82
7. Robust detection of non-overlapping ellipses from points with applications to circular target extraction in images and cylinder detection in point clouds p. 83-108
8. Meta-classification of remote sensing reflectance to estimate trophic status of inland and nearshore waters 109-126
9. Self-calibration dense bundle adjustment of multi-view Worldview-3 basic images p. 127-138
10. Video object detection with a convolutional regression tracker p. 139-150
11. Local and global encoder network for semantic segmentation of Airborne laser scanning point clouds p. 151-168
12. Symmetrical lattice generative adversarial network for remote sensing images compression p. 169-181
13. Statistical estimation of next-day nighttime surface urban heat islands p. 182-195
14. Satellite-based data fusion crop type classification and mapping in Rio Grande do Sul, Brazil p. 196-210
15. Adversarial unsupervised domain adaptation for 3D semantic segmentation with multi-modal learning p. 211-221
16. Spatio-temporal linking of multiple SAR satellite data from medium and high resolution Radarsat-2 images p. 222-236
17. FPS-Net: A convolutional fusion network for large-scale LiDAR point cloud segmentation p. 237-249
18. Mapping fine-scale human disturbances in a working landscape with Landsat time series on Google Earth Engine p. 250-261
19. Weakly supervised instance attention for multisource fine-grained object recognition with an application to tree species classification p. 262-274

M. 4594-12-2021

526.982

Perpustakaan BIG

Tersedia namun tidak untuk dipinjamkan - Missing

• Self-supervised monocular depth estimation from oblique UAV videos
• Classifying rock slope materials in photogrammetric point clouds using robust color and geometric features
• Radiative transfer modeling to measure fire impact and forest engineering resilience at short-term
• Learning deep cross-scale feature propagation for indoor semantic segmentation
• Juggling with representations: On the information transfer between imagery, point clouds, and meshes for multi-modal semantics
• A two-step mapping of irrigated corn with multi-temporal MODIS and Landsat analysis ready data
• Robust detection of non-overlapping ellipses from points with applications to circular target extraction in images and cylinder detection in point clouds
• Meta-classification of remote sensing reflectance to estimate trophic status of inland and nearshore waters
• Self-calibration dense bundle adjustment of multi-view Worldview-3 basic images
• Video object detection with a convolutional regression tracker
• Local and global encoder network for semantic segmentation of Airborne laser scanning point clouds
• Symmetrical lattice generative adversarial network for remote sensing images compression
• Statistical estimation of next-day nighttime surface urban heat islands
• Satellite-based data fusion crop type classification and mapping in Rio Grande do Sul, Brazil
• Adversarial unsupervised domain adaptation for 3D semantic segmentation with multi-modal learning
• Spatio-temporal linking of multiple SAR satellite data from medium and high resolution Radarsat-2 images
• FPS-Net: A convolutional fusion network for large-scale LiDAR point cloud segmentation
• Mapping fine-scale human disturbances in a working landscape with Landsat time series on Google Earth Engine
• Weakly supervised instance attention for multisource fine-grained object recognition with an application to tree species classification

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