SHADOW AND CLOUD MASKING FOR AGRICULTURE APPLICATIONS USING CONVOLUTIONAL NEURAL NETWORKS

A method for shadow and cloud masking for remote sensing images of an agricultural field using a convolutional neural network, the method includes electronically receiving an observed image, the observed image comprising a plurality of pixels and each of the pixels associated with corresponding band information and determining by a cloud mask generation module executing on the at least one processor a classification for each of the plurality of pixels in the observed image using the band information by applying a classification model, the classification model comprising a convolutional neural network comprising a plurality of layers of nodes. The cloud mask generation module applies a plurality of transformations to transform data between layers in the convolutional neural network to generate a cloud map.