APPLICATION OF DEEP LEARNING OF MULTI-TEMPORAL SENTINEL-1 IMAGES FOR THE CLASSIFICATION OF COASTAL VEGETATION ZONE OF THE DANUBE DELTA - Archive ouverte HAL
Communication Dans Un Congrès Année : 2018

APPLICATION OF DEEP LEARNING OF MULTI-TEMPORAL SENTINEL-1 IMAGES FOR THE CLASSIFICATION OF COASTAL VEGETATION ZONE OF THE DANUBE DELTA

Domaines

Géographie

Simona Niculescu  : Connectez-vous pour contacter le contributeur

https://hal.science/hal-01804954

Soumis le : vendredi 1 juin 2018-11:43:17

Dernière modification le : vendredi 19 avril 2024-16:18:56

Fichier non déposé

Dates et versions

hal-01804954 , version 1 (01-06-2018)

Identifiants

  • HAL Id : hal-01804954 , version 1

Citer

Simona Niculescu, Dino Ienco, Jenica Hanganu. APPLICATION OF DEEP LEARNING OF MULTI-TEMPORAL SENTINEL-1 IMAGES FOR THE CLASSIFICATION OF COASTAL VEGETATION ZONE OF THE DANUBE DELTA. Developments, Technologies and Applications in Remote Sensing / International Society of Photogrammetry and Remote Sensing, May 2018, Beijing, China. ⟨hal-01804954⟩

Exporter

BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite

Collections

CIRAD UNIV-BREST UNIV-NANTES AGROPARISTECH EPHE UR2-HB CNRS UNIV-ANGERS IRSTEA LETG LETG-GEOMER IUEM COMUE-NORMANDIE AGROPOLIS TETIS PSL UNIV-RENNES2 UNIV-RENNES UNICAEN IGARUN INRAE INRAEOCCITANIEMONTPELLIER NANTES-UNIVERSITE MATHNUM
238 Consultations
0 Téléchargements

Partager

More