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ISPRS Journal of Photogrammetry and Remote Sensing Volume 172 February 2021

Derek Lichti - Nama Orang;

1. Radiometric correction of laser scanning intensity data applied for terrestrial laser scanning p. 1-16
2. Per-pixel land cover accuracy prediction: A random forest-based method with limited reference sample data p. 17-27
3. Spruce budworm tree host species distribution and abundance mapping using multi-temporal Sentinel-1 and Sentinel-2 satellite imagery p. 28-40
4. Robust line feature matching based on pair-wise geometric constraints and matching redundancy p. 41-58
5. A novel surface water index using local background information for long term and large-scale Landsat images p. 59-78
6. Tropical forest canopy height estimation from combined polarimetric SAR and LiDAR using machine-learning p. 79-94
7. Multi-directional change detection between point clouds p. 95-113
8. An anchor-based graph method for detecting and classifying indoor objects from cluttered 3D point clouds p. 114-131
9. Comprehensive time-series analysis of bridge deformation using differential satellite radar interferometry based on Sentinel-1 p. 132-146
10. Digital surface model generation for drifting Arctic sea ice with low-textured surfaces based on drone images p. 147-159
11. Quality-based registration refinement of airborne LiDAR and photogrammetric point clouds p. 160-170
12. SceneNet: Remote sensing scene classification deep learning network using multi-objective neural evolution architecture search p. 171-188
13. Automated iceberg tracking with a machine learning approach applied to SAR imagery: A Weddell sea case study p. 189-206
14. Combining graph-cut clustering with object-based stem detection for tree segmentation in highly dense airborne lidar point clouds p. 207-222
15. GTP-PNet: A residual learning network based on gradient transformation prior for pansharpenin p. 223-239
16. Deep regression for LiDAR-based localization in dense urban areas p. 240-252
17. AMENet: Attentive Maps Encoder Network for trajectory prediction p. 253-256


Ketersediaan
M.4590-12-2021526.982Perpustakaan BIGTersedia namun tidak untuk dipinjamkan - Missing
Informasi Detail
Judul Seri
-
No. Panggil
526.982
Penerbit
Amsterdam : Elsevier., 2021
Deskripsi Fisik
266 hlm.: illus.; 28 cm.
Bahasa
Inggris
ISBN/ISSN
0924-2716
Klasifikasi
526.982
Tipe Isi
text
Tipe Media
unspecified
Tipe Pembawa
unspecified
Edisi
Vol. 172 February 2021
Subjek
-
Info Detail Spesifik
-
Pernyataan Tanggungjawab
Editor in chief Derek Lichti
Versi lain/terkait

Tidak tersedia versi lain

Lampiran Berkas
  • Radiometric correction of laser scanning intensity data applied for terrestrial laser scanning
  • Per-pixel land cover accuracy prediction: A random forest-based method with limited reference sample data
  • Spruce budworm tree host species distribution and abundance mapping using multi-temporal Sentinel-1 and Sentinel-2 satellite imagery
  • Robust line feature matching based on pair-wise geometric constraints and matching redundancy
  • A novel surface water index using local background information for long term and large-scale Landsat images
  • Tropical forest canopy height estimation from combined polarimetric SAR and LiDAR using machine-learning
  • Multi-directional change detection between point clouds
  • An anchor-based graph method for detecting and classifying indoor objects from cluttered 3D point clouds
  • Comprehensive time-series analysis of bridge deformation using differential satellite radar interferometry based on Sentinel-1
  • Digital surface model generation for drifting Arctic sea ice with low-textured surfaces based on drone images
  • Quality-based registration refinement of airborne LiDAR and photogrammetric point clouds
  • SceneNet: Remote sensing scene classification deep learning network using multi-objective neural evolution architecture search
  • Automated iceberg tracking with a machine learning approach applied to SAR imagery: A Weddell sea case study
  • Combining graph-cut clustering with object-based stem detection for tree segmentation in highly dense airborne lidar point clouds
  • GTP-PNet: A residual learning network based on gradient transformation prior for pansharpenin
  • Deep regression for LiDAR-based localization in dense urban areas
  • AMENet: Attentive Maps Encoder Network for trajectory prediction
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