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      <image:title>Blog - The Pandora’s box that is ML</image:title>
      <image:caption>At this point, the current version of the model is based on Sentinel-2 satellite images, with this data being presented to the model at a resolution of 10m*10m. The model is built in Benin and can be used within an area of 200,000 sqkm around the area it was trained. The model is currently able to identify cashew at an accuracy of 84% and can easily be recreated for another area once training data for that particular new area has been made available.</image:caption>
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      <image:title>Blog - The Pandora’s box that is ML - Make it stand out</image:title>
      <image:caption>ML identified cashew</image:caption>
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    <loc>https://fieldy.space/blog/intern-turned-front-end-dev</loc>
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      <image:title>Blog - Finding seasonal crops</image:title>
      <image:caption>Rice mapping was carried out using Synthetic-Aperture Radar (SAR) data. SAR data represents the backscattered signals reflected from the earth's surface. The backscatter is affected by the size and structure of the objects such as vegetation on the earth's surface and the moisture content. For example, when the SAR signals from a sea are compared with those from a vegetated area, the signals reflected from the sea will be much lower than those reflected from the vegetated area.</image:caption>
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