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8989
9090## Objectives
9191
92- Our objective in this application is two-fold . First, we would like to assign
93- a categorical value for each " pixel" of the image as a label for [ geostatistical
94- learning ] ( https://www.frontiersin.org/articles/10.3389/fams.2021.689393/full )
95- tasks. Second, we would like to convert the region of the image that is inside
96- of the agricultural field into a polygonal area for measurements of area and
97- perimeter.
92+ Our objective is twofold . First, we would like to assign a categorical value
93+ for each pixel of the image, which is true inside of the agricultural field and
94+ false outside. This value (a.k.a. label) can be useful in applications of
95+ [ geostatistical learning ] ( https://www.frontiersin.org/articles/10.3389/fams.2021.689393/full ) .
96+ Second, we would like to convert the region of the image that is inside of the
97+ agricultural field into a polygonal area for measurements of area and perimeter.
9898
9999## Methodology
100100
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