Auflistung nach Schlagwort "deep learning; precision agriculture; crop yield; explainable artificial intelligence; spatial cross validation; self-supervised learning"
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- TextdokumentUnderstanding Agricultural Landscape Dynamics with Explainable Artificial Intelligence(DC@KI2023: Proceedings of Doctoral Consortium at KI 2023, 2023) Stiller, StefanDeep learning (DL) models, particularly those utilizing computer vision techniques such as proximal and remote sensing imagery, have witnessed extensive utilization within agriculture [KPB18]. These DL applications encompass diverse areas, including land cover and crop type mapping [Ku17], crop yield estimation [KS15, NNL19], drought monitoring [Sh19], plant disease spread analysis [Te20], and overall monitoring of agricultural systems. DL applications offer significant potential to enhance agricultural practices at various scales, spanning from individual organisms, field, landscape, to regional and even continental scales [Ry22b].