1 citations · 1 across the 4 of their papers we have counts for
6 papers
Deep semi-supervised approach based on consistency regularization and similarity learning for weeds classification
Farouq Benchallal, Adel Hafiane, Nicolas Ragot +1
Weed species classification represents an important step for the development of automated targeting systems that allow the adoption of precision agriculture practices. To reduce co…
WGAST: Weakly-Supervised Generative Network for Daily 10 m Land Surface Temperature Estimation via Spatio-Temporal Fusion
Sofiane Bouaziz, Adel Hafiane, Raphael Canals +1
Urbanization, climate change, and agricultural stress are increasing the demand for precise and timely environmental monitoring. Land Surface Temperature (LST) is a key variable in…
FuseTen: A Generative Model for Daily 10 m Land Surface Temperature Estimation from Spatio-Temporal Satellite Observations
Sofiane Bouaziz, Adel Hafiane, Raphael Canals +1
Urban heatwaves, droughts, and land degradation are pressing and growing challenges in the context of climate change. A valuable approach to studying them requires accurate spatio-…
Loss-Guided Model Sharing and Local Learning Correction in Decentralized Federated Learning for Crop Disease Classification
Denis Mamba Kabala, Adel Hafiane, Laurent Bobelin +1
Crop disease detection and classification is a critical challenge in agriculture, with major implications for productivity, food security, and environmental sustainability. While d…
Enhancing DeepLabV3+ to Fuse Aerial and Satellite Images for Semantic Segmentation
Anas Berka, Mohamed El Hajji, Raphael Canals +2
Aerial and satellite imagery are inherently complementary remote sensing sources, offering high-resolution detail alongside expansive spatial coverage. However, the use of these so…
Deep Learning for Spatio-Temporal Fusion in Land Surface Temperature Estimation: A Comprehensive Survey, Experimental Analysis, and Future Trends
Sofiane Bouaziz, Adel Hafiane, Raphael Canals +1
Land Surface Temperature (LST) plays a key role in climate monitoring, urban heat assessment, and land-atmosphere interactions. However, current thermal infrared satellite sensors…