Thomas Di Martino

Orcid: 0000-0002-4853-3987

According to our database1, Thomas Di Martino authored at least 9 papers between 2021 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

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Bibliography

2024
Unsupervised Deep Learning for vegetation monitoring using C-Band SAR time series : from agriculture to boreal forests. (Apprentissage profond non-supervisé pour le suivi de végétation à partir de séries temporelles SAR en bande C : de l'agriculture aux forêts boréales).
PhD thesis, 2024

Convolutional Autoencoder Applied to Short SAR Time Series for Under Canopy Object Detection.
Proceedings of the IGARSS 2024, 2024

2023
Detection of Forest Fires through Deep Unsupervised Learning Modeling of Sentinel-1 Time Series.
ISPRS Int. J. Geo Inf., August, 2023

FARMSAR: Fixing AgRicultural Mislabels Using Sentinel-1 Time Series and AutoencodeRs.
Remote. Sens., January, 2023

Grad-SLAM: Explaining Convolutional Autoencoders' Latent Space of Satellite Image Time Series.
IEEE Geosci. Remote. Sens. Lett., 2023

Towards the Understanding of the C-Band Temporal Signature of Boreal Forest Through Physiology Parameters Retrieval from Sentinel-1 Time Series and Machine Learning.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2023

2022
Beets or Cotton? Blind Extraction of Fine Agricultural Classes Using a Convolutional Autoencoder Applied to Temporal SAR Signatures.
IEEE Trans. Geosci. Remote. Sens., 2022

2021
Multi-Branch Deep Learning Model for Detection of Settlements Without Electricity.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2021

Convolutional Autoencoder for Unsupervised Representation Learning of PolSAR Time-Series.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2021


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