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Advanced Deep Learning Architectures for Accurate Detection of Subsurface Tile Drainage Pipes from Remote Sensing Images. (arXiv:2210.02071v3 [cs.CV] UPDATED)
Nov. 2, 2022, 1:12 a.m. | Tom-Lukas Breitkopf (1), Leonard W. Hackel (1), Mahdyar Ravanbakhsh (1), Anne-Karin Cooke (2), Sandra Willkommen (2), Stefan Broda (2), Begüm Dem
cs.LG updates on arXiv.org arxiv.org
Subsurface tile drainage pipes provide agronomic, economic and environmental
benefits. By lowering the water table of wet soils, they improve the aeration
of plant roots and ultimately increase the productivity of farmland. They do
however also provide an entryway of agrochemicals into subsurface water bodies
and increase nutrition loss in soils. For maintenance and infrastructural
development, accurate maps of tile drainage pipe locations and drained
agricultural land are needed. However, these maps are often outdated or not
present. Different remote …
advanced architectures arxiv deep learning detection images remote sensing
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