High throughput image analysis is a rapidly growing industry and its success is largely due to significant advancements in machine learning as well as the ubiquity of affordable imaging platforms. High throughput image analysis is about the automated capture of large numbers of images and video which are then used for scientific research and machine learning use cases. This type of mass data capture is typically done in biological use cases to help average out variability in an experiment (e.g. one plant may die due to a bad seed, but 10 shouldn’t). Other use cases are in Medical Imaging, Satellite Imaging and Agriculture.
Large quantities of images are difficult to work with for several technical reasons which mean there is no simple way to manage and view them all. In most cases, the only solution is to instead extract pieces of information from them in an automated way, while the original, high fidelity images are never viewed.
Due to the complexity and perceived uniqueness of the problem, many companies invest technical resources into developing-house solutions. These efforts usually turn out to be more complicated than originally thought and divert time and energy away from higher value projects within the business/institution.