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Daniele Marinelli
Daniele Marinelli
Email verificata su fmach.it - Home page
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Citata da
Citata da
Anno
A Review of Change Detection in Multitemporal Hyperspectral Images: Current Techniques, Applications, and Challenges
S Liu, D Marinelli, L Bruzzone, F Bovolo
IEEE Geoscience and Remote Sensing Magazine 7 (2), 140-158, 2019
2612019
Automatic Pleural Line Extraction and COVID-19 Scoring from Lung Ultrasound Data
L Carrer, E Donini, D Marinelli, M Zanetti, F Mento, E Torri, A Smargiassi, ...
IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control 67 …, 2020
782020
A novel change detection method for multitemporal hyperspectral images based on binary hyperspectral change vectors
D Marinelli, F Bovolo, L Bruzzone
IEEE Transactions on Geoscience and Remote Sensing 57 (7), 4913-4928, 2019
732019
A Novel Approach to 3-D Change Detection in Multitemporal LiDAR Data Acquired in Forest Areas
D Marinelli, C Paris, L Bruzzone
IEEE Transactions on Geoscience and Remote Sensing, 2018
412018
ExtremeEarth meets satellite data from space
DH Hagos, T Kakantousis, V Vlassov, S Sheikholeslami, T Wang, ...
IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2021
132021
An approach based on deep learning for tree species classification in lidar data acquired in mixed forest
D Marinelli, C Paris, L Bruzzone
IEEE Geoscience and Remote Sensing Letters 19, 1-5, 2022
112022
A novel method for unsupervised multiple Change Detection in hyperspectral images based on binary Spectral Change Vectors
D Marinelli, F Bovolo, L Bruzzone
Analysis of Multitemporal Remote Sensing Images (MultiTemp), 2017 9th …, 2017
102017
A system for burned area detection on multispectral imagery
M Zanetti, S Saha, D Marinelli, ML Magliozzi, M Zavagli, M Costantini, ...
IEEE Transactions on Geoscience and Remote Sensing 60, 1-15, 2021
92021
An Approach to Tree Detection Based on the Fusion of Multitemporal LiDAR Data
D Marinelli, C Paris, L Bruzzone
IEEE Geoscience and Remote Sensing Letters 16 (11), 1771-1775, 2019
92019
Fusion of high and very high density lidar data for 3d forest change detection
D Marinelli, C Paris, L Bruzzone
2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS …, 2016
82016
A high resolution burned area detector for Sentinel-2 and Landsat-8
M Zanetti, D Marinelli, M Bertoluzza, S Saha, F Bovolo, L Bruzzone, ...
2019 10th International Workshop on the Analysis of Multitemporal Remote …, 2019
72019
A novel change detection method for multitemporal hyperspectral images based on a discrete representation of the change information
D Marinelli, F Bovolo, L Bruzzone
2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS …, 2017
62017
Spectral separability of bark beetle infestation stages: A single-tree time-series analysis using Planet imagery
M Dalponte, R Cetto, D Marinelli, D Andreatta, C Salvadori, F Pirotti, ...
Ecological Indicators 153, 110349, 2023
52023
Forest Change Detection in Lidar Data Based on Polar Change Vector Analysis
D Marinelli, NC Coops, DK Bolton, L Bruzzone
IEEE Geoscience and Remote Sensing Letters 19, 1-5, 2020
52020
Crop Water Availability Mapping in the Danube Basin Based on Deep Learning, Hydrological and Crop Growth Modelling
S Migdall, S Dotzler, E Gleisberg, F Appel, M Muerth, H Bach, ...
Engineering Proceedings 9 (1), 42, 2022
42022
A Triangulation-Based Technique for Tree-Top Detection in Heterogeneous Forest Structures Using High Density LiDAR Data
D Marinelli, C Paris, L Bruzzone
IEEE Geoscience and Remote Sensing Letters 19, 1-5, 2021
42021
Artificial Intelligence and big data technologies for Copernicus data: The EXTREMEEARTH project
M Koubarakis, G Stamoulis, D Bilidas, T Ioannidis, G Mandilaras, ...
Conference on Big Data from Space, BiDS 2021: From Insights to Foresight, 9-12, 2021
42021
An Unsupervised Change Detection Method for Lidar Data in Forest Areas Based on Change Vector Analysis in the Polar Domain
D Marinelli, NC Coops, DK Bolton, L Bruzzone
IGARSS 2018-2018 IEEE International Geoscience and Remote Sensing Symposium …, 2018
42018
Water stress assessment in Austria based on deep learning and crop growth modelling
S Migdall, S Dotzler, C Miesgang, F Appel, M Muerth, H Bach, ...
Conference on Big Data from Space, BiDS 2021: From Insights to Foresight, 69-72, 2021
32021
Advanced Methods for Change Detection in LiDAR Data and Hyperspectral Images
D Marinelli
University of Trento, 2019
32019
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