An Image Processing Approach for Weed Detection Using Deep Convolutional Neural Network

According to weeds increased competition with crops, they have been given responsible for 45% of crop losses in the agricultural industry. This percentage can be decreased with an effective method of weed detection. The conventional weeding techniques take a long time and largely require manual labor. So, this process has to be automated. As a result, an image processing approach for weed detection implementing Deep Convolutional Neural Network is provided in this analysis. The purpose of this study, the possibilities of classifying and detecting weeds from Unmanned Aerial Vehicle (UAV) images using deep learning techniques. The presented method will achieve high accuracy when compared to state-of-the-art algorithms.