In this work, a model for the characterization of microalgae cultures
based on artificial neural networks has been developed. Data acquisition
has been performed using FlowCam, a device capable of capturing images
of the cells detected in a culture sample, which are used as inputs by
the model. The model can distinguish between 6 different genera of
microalgae, having been trained with several species of each genus. It
was further complemented with a classification threshold to discard
unwanted objects while improving the overall accuracy of the model. The
results demonstrate the accuracy of the Deep Learning models for the
characterization of microalgae cultures, it being a useful tool for the
monitoring of microalgae cultures in large-scale production facilities.