TH3.P3.3
SwinUNet for Segmentation of Vineyards and Olive Orchards in Sentinel-2 Images
Danilo Leite, Miguel Fernandes, Luís Pádua, Pedro Marques, Joaquim J. Sousa, Raul Morais, Antonio Cunha, University of Trás-os-Montes and Alto Douro, Portugal
Session:
TH3.P3: Crop Classifications I Oral
Track:
Land Applications
Location:
Room P3
Presentation Time:
Thursday, 7 August, 13:45 - 14:00
Presentation
Discussion
Resources
No resources available.
Session TH3.P3
TH3.P3.1: TOWARDS CROSS-YEAR KNOWLEDGE TRANSFER FOR CROP CLASSIFICATION: A PERSPECTIVE FROM LLM-ASSISTED ACTIVE LEARNING
Xingli Qin, Bingfang Wu, Miao Zhang, Hongwei Zeng, Mengxiao Li, Fuyou Tian, Key Laboratory of Remote Sensing and Digital Earth, Aerospace Information Research Institute, Chinese Academy of Sciences, China
TH3.P3.2: INTEGRATING MACHINE LEARNING AND OBIA FOR AGRICULTURAL LAND COVER CLASSIFICATION: A CASE STUDY IN NORTHEASTERN PORTUGAL
Pedro Marques, Luís Pádua, Emanuel Peres, Raul Morais, Anabela Fernandes-Silva, Joaquim J. Sousa, University of Trás-os-Montes e Alto Douro, Portugal
TH3.P3.3: SwinUNet for Segmentation of Vineyards and Olive Orchards in Sentinel-2 Images
Danilo Leite, Miguel Fernandes, Luís Pádua, Pedro Marques, Joaquim J. Sousa, Raul Morais, Antonio Cunha, University of Trás-os-Montes and Alto Douro, Portugal
TH3.P3.5: EVALUATION OF SENTINEL-2 SATELLITE IMAGES TO STUDY THE SPATIAL VARIABILITY IN RICE FIELDS FOR PRECISION FARMING
Thomas M. Koutsos, Maria Kalitsiou, Nikolaos Gkoutas, Thomas K. Alexandridis, Aristotle University of Thessaloniki, Greece
Resources
No resources available.