Currently, uniform spraying of herbicides is the primary practice in agriculture because it is economically feasible but is also environmentally unsafe. Precision weed management practices reduce the amount of herbicide needed by spraying specifically on weeds. The purpose of this study was to explore standard pre-trained Convolutional Neural Networks (CNN) to detect weeds with the top-performing CNN used as the classifier in a region-based convolution neural network (RCNN) and presenting the methodology and results as an alternative solution to current weed management practices.