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Semi-Supervised Deep Learning Representations in Earth Observation Based Forest Management.

, , , , , , , , , and . IGARSS, page 650-653. IEEE, (2023)

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Forest stem volume and storm damage mapping in Finland and Russia., , , and . IGARSS, page 2309-2312. IEEE, (2014)Comparison and evaluation of polarimetric change detection techniques in aerial SAR data., and . IGARSS, page 2386-2389. IEEE, (2007)Comparison of Polarimetric Change Detection Methods on ALOS PALSAR Images over Finland., , and . IGARSS (5), page 377-380. IEEE, (2008)Relasphone - Mobile and Participative In Situ Forest Biomass Measurements Supporting Satellite Image Mapping., , , , , , and . Remote. Sens., 8 (10): 869 (2016)A lightweight deep learning based cloud detection method for Sentinel-2A imagery fusing multi-scale spectral and spatial features., , , , , , , and . CoRR, (2021)Timely And Semi-Automatic Detection of Forest Logging Events in Boreal Forest Using All Available Landsat Data., , , and . IGARSS, page 1730-1733. IEEE, (2018)Self-Attentive Generative Adversarial Network for Cloud Detection in High Resolution Remote Sensing Images., , , , and . IEEE Geosci. Remote. Sens. Lett., 17 (10): 1792-1796 (2020)Semi-Supervised Deep Learning Representations in Earth Observation Based Forest Management., , , , , , , , , and . IGARSS, page 650-653. IEEE, (2023)Participative forest in-situ measurements for biomass mapping in satellite images over Durango State, Mexico., , , , , and . IGARSS, page 5391-5394. IEEE, (2015)3D-Connected Components Analysis for Traffic Monitoring in Image Sequences Acquired from a Helicopter., , and . SCIA, volume 3540 of Lecture Notes in Computer Science, page 141-150. Springer, (2005)