Conference Paper

Sorghum Yield Prediction using Machine Learning

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Abstract

Estimation of a future agricultural production is an important challenge for farmers. In this paper, we propose a system based on machine learning algorithms to estimate farm yields. The experiments were conducted on a Sorghum field. We use TensorFlow with Convolutional Neural Networks and Linear Regression. These algorithms allow us 1) to detect the different ears of Sorghum on an image and 2) to estimate their weight.

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... The yield prediction can be defined from the earlier dataset and what type of latest technologies available and applicable on all the ways based on the current crop, climatic and financial situations for improving the yield. A study [28] used Tensor Flow with Convolutional Neural Networks and Linear Regression for estimating the yield from Sorghum field. ...
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