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IJSTR >> Volume 9 - Issue 3, March 2020 Edition



International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616



Automated Weed Removal System Using Convolutional Neural Network

[Full Text]

 

AUTHOR(S)

S.Manoruthra, Dr.V.Kalaivani, Dr. Felix Joseph, Dr.B.L.Velammal

 

KEYWORDS

Weed Classification, Shape Features, Contour property, Convolutional Neural Network.

 

ABSTRACT

Weed removal process is a vital part in the agricultural fields. The usual way to remove the weed is time-consuming and also requires more manual labor work. The aim is to remove the weeds in agriculture fields automatically. The proposed work is used to detect the weed which is grown between crops using a deep learning technique and remove the weeds by an automatic cutter. The deep learning is used to analyze the relevant features from the agricultural images. The dataset is trained for the classification of weed and crop. In deep learning Convolutional Neural Network(CNN) uses the convolutional layer with a ReLU function for extracting the features of an image and uses a max-pooling and fully connected layer with ReLU to classify the weed from the crop. The pre-processed image is applied to the CNN network. From the resultant image, Region Of Interest(ROI) is extracted and also extract some features for training. After training, the classification is done. Thus the weed is detected using a deep learning network. In this,100 images are trained to improve accuracy.

 

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