| UAV for 3D mapping applications: a review F Nex, F Remondino Applied geomatics 6, 1-15, 2014 | 1728 | 2014 |
| UAV photogrammetry for mapping and 3d modeling–current status and future perspectives F Remondino, L Barazzetti, F Nex, M Scaioni, D Sarazzi The International Archives of the Photogrammetry, Remote Sensing and Spatial …, 2012 | 936 | 2012 |
| State of the art in high density image matching F Remondino, MG Spera, E Nocerino, F Menna, F Nex The photogrammetric record 29 (146), 144-166, 2014 | 598 | 2014 |
| Review of the current state of UAV regulations C Stöcker, R Bennett, F Nex, M Gerke, J Zevenbergen Remote sensing 9 (5), 459, 2017 | 475 | 2017 |
| Disaster damage detection through synergistic use of deep learning and 3D point cloud features derived from very high resolution oblique aerial images, and multiple-kernel-learning A Vetrivel, M Gerke, N Kerle, F Nex, G Vosselman ISPRS journal of photogrammetry and remote sensing 140, 45-59, 2018 | 257 | 2018 |
| UAV and RPV systems for photogrammetric surveys in archaelogical areas: two tests in the Piedmont region (Italy) F Chiabrando, F Nex, D Piatti, F Rinaudo Journal of archaeological science 38 (3), 697-710, 2011 | 215 | 2011 |
| Performance analysis of the SIFT operator for automatic feature extraction and matching in photogrammetric applications A Lingua, D Marenchino, F Nex Sensors 9 (05), 3745-3766, 2009 | 184 | 2009 |
| Review of automatic feature extraction from high-resolution optical sensor data for UAV-based cadastral mapping S Crommelinck, R Bennett, M Gerke, F Nex, MY Yang, G Vosselman Remote Sensing 8 (8), 689, 2016 | 156 | 2016 |
| The use of remotely piloted aircraft systems (RPASs) for natural hazards monitoring and management D Giordan, Y Hayakawa, F Nex, F Remondino, P Tarolli Natural hazards and earth system sciences 18 (4), 1079-1096, 2018 | 148 | 2018 |
| ISPRS benchmark for multi-platform photogrammetry F Nex, M Gerke, F Remondino, HJ Przybilla, M Bäumker, A Zurhorst ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information …, 2015 | 123 | 2015 |
| UAV-based structural damage mapping: A review N Kerle, F Nex, M Gerke, D Duarte, A Vetrivel ISPRS international journal of geo-information 9 (1), 14, 2019 | 110 | 2019 |
| Using UAVs for map creation and updating. A case study in Rwanda M Koeva, M Muneza, C Gevaert, M Gerke, F Nex Survey Review 50 (361), 312-325, 2018 | 95 | 2018 |
| SATELLITE IMAGE CLASSIFICATION OF BUILDING DAMAGES USING AIRBORNE AND SATELLITE IMAGE SAMPLES IN A DEEP LEARNING APPROACH. D Duarte, F Nex, N Kerle, G Vosselman ISPRS Annals of Photogrammetry, Remote Sensing & Spatial Information …, 2018 | 93 | 2018 |
| Dense image matching: Comparisons and analyses F Remondino, MG Spera, E Nocerino, F Menna, F Nex, ... 2013 Digital Heritage International Congress (DigitalHeritage) 1, 47-54, 2013 | 93 | 2013 |
| Use of unmanned aerial vehicles in monitoring application and management of natural hazards D Giordan, A Manconi, F Remondino, F Nex Geomatics, Natural Hazards and Risk 8 (1), 1-4, 2017 | 92 | 2017 |
| Structural building damage detection with deep learning: Assessment of a state-of-the-art CNN in operational conditions F Nex, D Duarte, FG Tonolo, N Kerle Remote sensing 11 (23), 2765, 2019 | 89 | 2019 |
| Aerial multi-camera systems: Accuracy and block triangulation issues E Rupnik, F Nex, I Toschi, F Remondino ISPRS Journal of Photogrammetry and Remote Sensing 101, 233-246, 2015 | 83 | 2015 |
| Towards real-time building damage mapping with low-cost UAV solutions F Nex, D Duarte, A Steenbeek, N Kerle Remote sensing 11 (3), 287, 2019 | 76 | 2019 |
| Oblique multi-camera systems-orientation and dense matching issues E Rupnik, F Nex, F Remondino EuroCOW, 2014 | 75 | 2014 |
| Multi-resolution feature fusion for image classification of building damages with convolutional neural networks D Duarte, F Nex, N Kerle, G Vosselman Remote sensing 10 (10), 1636, 2018 | 71 | 2018 |
Fabio Remondino3D Optical Metrology - Bruno Kessler FoundationVerified email at fbk.eu
