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Francesco Nex
Francesco Nex
University of Twente - ITC Faculty
Verified email at utwente.nl - Homepage
Title
Cited by
Cited by
Year
UAV for 3D mapping applications: a review
F Nex, F Remondino
Applied geomatics 6, 1-15, 2014
21182014
UAV photogrammetry for mapping and 3D modeling: Current status and future perspectives
F Remondino, L Barazzetti, FC Nex, M Scaioni, D Sarazzi
Proceedings of the International Conference on Unmanned Aerial Vehicle in …, 2011
11112011
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
6982014
Review of the current state of UAV regulations
C Stöcker, R Bennett, F Nex, M Gerke, J Zevenbergen
Remote sensing 9 (5), 459, 2017
6512017
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
3402018
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
2412011
UAV in the advent of the twenties: Where we stand and what is next
F Nex, C Armenakis, M Cramer, DA Cucci, M Gerke, E Honkavaara, ...
ISPRS journal of photogrammetry and remote sensing 184, 215-242, 2022
2132022
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
2052016
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
2012009
Lite-mono: A lightweight cnn and transformer architecture for self-supervised monocular depth estimation
N Zhang, F Nex, G Vosselman, N Kerle
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023
1972023
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
1952018
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
1782019
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
1662019
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
1502015
Real-time semantic segmentation with context aggregation network
MY Yang, S Kumaar, Y Lyu, F Nex
ISPRS journal of photogrammetry and remote sensing 178, 124-134, 2021
143*2021
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 the Photogrammetry, Remote Sensing and Spatial Information …, 2018
1382018
Accuracy assessment of real-time kinematics (RTK) measurements on unmanned aerial vehicles (UAV) for direct geo-referencing
D Ekaso, F Nex, N Kerle
Geo-spatial information science 23 (2), 165-181, 2020
1342020
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
1272018
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
1152017
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
1142019
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