Crop and Weed Classification Using Deep Learning

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R. Kingsy Grace, et. al.

Abstract

Information technology is prominent in precision agriculture and also support the agronomist in agro business. Usually, weeds grow along with the crops and reduces the yield of that crop. Herbicides are used to remove the weeds. Without the identification of the type of the weed, the herbicide may damage the crop too. It is necessary to identify and classify the weeds from the farms in order to control them. Deep learning-based computer vision technique, Conv Net or CNN is used to analyse images. This paper proposed a CNN based deep learning model to identify the weeds and crops from the farm field. Based on the predictions the type of herbicide will be suggested to the farmers.


 

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How to Cite
et. al., R. K. G. . (2021). Crop and Weed Classification Using Deep Learning. Turkish Journal of Computer and Mathematics Education (TURCOMAT), 12(7), 935–938. Retrieved from https://turcomat.org/index.php/turkbilmat/article/view/2678
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