AUTOMATED FOAM DETECTION

A computer implemented method for detecting foam on the surface of a liquid medium contained in a vessel is described. The method including the steps of receiving a sample image of at least a portion of the vessel comprising the liquid-gas interface and classifying the sample image between a first class and at least one second class, associated with different amounts of foam on the surface of the liquid. The classifying is performed by a deep neural network classifier that has been trained using a plurality of training images of at least a portion of a vessel comprising a liquid-gas interface. The plurality of training images may comprise at least some images that differ from each other by one or more of: the location of the liquid-gas interface on the image, the polar and/or azimuthal angle at which the liquid-gas interface is viewed on the image, and the light intensity or colour temperature of the one or more light sources that illuminated the imaged portion of the vessel when the image was acquired. Related methods for controlling a bioprocess, for providing a tool, and related systems and computer software products are also described.