Abstract: A method of selective spraying in a selective-spray system that includes a spray boom attached to an agricultural vehicle, the spray boom including a plurality of cameras and a plurality of selective-spray nozzles. The method includes capturing, with each camera, a respective image of a respective region of an agricultural field, each region at a predetermined distance from the spray boom, each image associated with a respective selective-spray nozzle; automatically analyzing, with a computer, each image for a presence of at least one weed; automatically detecting, with the computer, the at least one weed in one or more images; and automatically selectively spraying one or more of the respective regions of the agricultural field using one or more of the selective-spray nozzles according to the one or more images where the at least one weed is detected.

Abstract: A system includes an agricultural vehicle, one or more cameras in mechanical communication with the agricultural vehicle, and a computer in electrical communication with the cameras. The computer is programmed to automatically analyze each image for a presence of at least one target plant using a trained machine-learning model, the trained machine-learning model having been trained with first images that include the at least one target plant and second images that do not include the at least one target plant; automatically detect, using the trained machine-learning model, the at least one target plant in a subset of the images; apply an image-selection parameter to the subset of the images to select one or more images for storage; and store the one or more images for machine-learning training in a computer storage device operably coupled to the one or more microprocessors.