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Diego Marcos
Diego Marcos
Junior Professor at Inria, Montpellier
Zweryfikowany adres z inria.fr - Strona główna
Tytuł
Cytowane przez
Cytowane przez
Rok
Detecting mammals in UAV images: Best practices to address a substantially imbalanced dataset with deep learning
B Kellenberger, D Marcos, D Tuia
Remote sensing of environment 216, 139-153, 2018
3442018
Rotation equivariant vector field networks
D Marcos, M Volpi, N Komodakis, D Tuia
International Conference on Computer Vision (ICCV), 2017
3152017
Land cover mapping at very high resolution with rotation equivariant CNNs: Towards small yet accurate models
D Marcos, M Volpi, B Kellenberger, D Tuia
ISPRS journal of photogrammetry and remote sensing 145, 96-107, 2018
2742018
RSVQA: Visual question answering for remote sensing data
S Lobry, D Marcos, J Murray, D Tuia
IEEE Transactions on Geoscience and Remote Sensing 58 (12), 8555-8566, 2020
2252020
Learning deep structured active contours end-to-end
D Marcos, D Tuia, B Kellenberger, L Zhang, M Bai, R Liao, R Urtasun
Proceedings of the IEEE conference on computer vision and pattern …, 2018
2052018
Learning rotation invariant convolutional filters for texture classification
D Marcos, M Volpi, D Tuia
2016 23rd International Conference on Pattern Recognition (ICPR), 2012-2017, 2016
1962016
Half a percent of labels is enough: Efficient animal detection in UAV imagery using deep CNNs and active learning
B Kellenberger, D Marcos, S Lobry, D Tuia
IEEE Transactions on Geoscience and Remote Sensing 57 (12), 9524-9533, 2019
1392019
A deep learning framework for matching of SAR and optical imagery
LH Hughes, D Marcos, S Lobry, D Tuia, M Schmitt
ISPRS Journal of Photogrammetry and Remote Sensing 169, 166-179, 2020
1222020
Semantic segmentation of remote sensing images with sparse annotations
Y Hua, D Marcos, L Mou, XX Zhu, D Tuia
IEEE Geoscience and Remote Sensing Letters 19, 1-5, 2021
1172021
Spatial and temporal deep learning methods for deriving land-use following deforestation: A pan-tropical case study using Landsat time series
RN Masolele, V De Sy, M Herold, D Marcos, J Verbesselt, F Gieseke, ...
Remote Sensing of Environment 264, 112600, 2021
922021
DeSpeckNet: Generalizing deep learning-based SAR image despeckling
AG Mullissa, D Marcos, D Tuia, M Herold, J Reiche
IEEE Transactions on Geoscience and Remote Sensing 60, 1-15, 2020
812020
Multi-temporal and multi-source remote sensing image classification by nonlinear relative normalization
D Tuia, D Marcos, G Camps-Valls
ISPRS Journal of Photogrammetry and Remote Sensing 120, 1-12, 2016
712016
Interpretability of deep learning models for crop yield forecasting
D Paudel, A De Wit, H Boogaard, D Marcos, S Osinga, IN Athanasiadis
Computers and Electronics in Agriculture 206, 107663, 2023
672023
Self-supervised pre-training enhances change detection in Sentinel-2 imagery
M Leenstra, D Marcos, F Bovolo, D Tuia
Pattern Recognition. ICPR International Workshops and Challenges: Virtual …, 2021
672021
Scale equivariance in CNNs with vector fields
D Marcos, B Kellenberger, S Lobry, D Tuia
ICML Workshops, 2018
642018
Social media and deep learning capture the aesthetic quality of the landscape
I Havinga, D Marcos, PW Bogaart, L Hein, D Tuia
Scientific reports 11 (1), 20000, 2021
432021
Geospatial Correspondences for Multimodal Registration
D Marcos, R Hamid, D Tuia
Computer Vision and Pattern Recognition (CVPR), 2016
402016
Contextual Semantic Interpretability
D Marcos, R Fong, S Lobry, R Flamary, N Courty, D Tuia
ACCV 2020, 2020
362020
When a few clicks make all the difference: Improving weakly-supervised wildlife detection in UAV images
B Kellenberger, D Marcos, D Tuia
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019
362019
Semantically Interpretable Activation Maps: what-where-how explanations within CNNs
D Marcos, S Lobry, D Tuia
2019 ICCV Workshop on Interpreting and Explaining Visual Artificial …, 2019
332019
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