System and method for plant disease detection support

Abstract

A computer-implemented method, computer program product and computer system () for detecting plant diseases. The system stores a convolutional neural network () trained with a multi-crop dataset. The convolutional neural network () has an extended topology comprising an image branch () based on a classification convolutional neural network for classifying the input images according to plant disease specific features, a crop identification branch () for adding plant species information, and a branch integrator for integrating the plant species information with each input image. The plant species information () specifies the crop on the respective input image (). The system receives a test input comprising an image () of a particular crop () showing one or more particular plant disease symptoms, and further receives a respective crop identifier () associated with the test input via an interface (). A classifier module () of the system applies the trained convolutional network () to the received test input, and provides a classification result (CR) according to the output vector of the convolutional neural network (). The classification result (CR) indicates the one or more plant diseases associated with the one or more particular plant disease symptoms.