Crop weed detection using artificial neural networks

Crop weed detection using artificial neural networks

This study implements a method that can identify crops and weeds using an Artificial Neural Network. It does this by evaluating images captured with the aid of Farm Bot and using FarmBot weed identification. The images were precisely captured using FarmBot’s technology and then processed in Matlab....

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Hauptverfasser: Nuthakki, Ramesh, Gowri, S. G. Mangala, Satyasrikanth
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Artificial neural networks
Crop identification
Weeds
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Gowri, S. G. Mangala
Satyasrikanth
description This study implements a method that can identify crops and weeds using an Artificial Neural Network. It does this by evaluating images captured with the aid of Farm Bot and using FarmBot weed identification. The images were precisely captured using FarmBot’s technology and then processed in Matlab. Weed associations were returned after the Artificial Neural Network was trained and utilised for picture re-casting of crops and weeds. At last, the network is trained to attain the accuracy and loss percentages. A validation accuracy of 83.33% and a prototype time of about 13 minutes are both provided by the trained network. More fresh photographs are considered, and ultimate correctness is achieved, as a consequence of this.
doi_str_mv 10.1063/5.0212115
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subjects Artificial neural networks
Crop identification
Weeds
title Crop weed detection using artificial neural networks
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