Choosing the right system integrator for Machine Vision and Deep Learning Projects

David Dechow:
For an end user to approach selecting a systems integrator in the machine vision marketplace, as well as one experienced in deep learning technology, in addition to the broader field of machine vision, some of the important things kind of cross over. The idea that the integrator should have familiarity with an industrial environment, have skills in applying industrial automation, and industrial automation components on the plant floor, and that imaging component, the knowledge of how to correctly image a particular part on an assembly line, particular part handled by a robot, or all of the variations of how imaging will be challenging on the plant floor. And then following up on the other end, being able to have some experience or gaining some experience in the application of machine vision and the context of particularly labeling, collaborative labeling, expert labeling of the content, the understanding that they need to get the best data possible, the best quality data possible, to ease and speed up the integration process and the implementation process for the customer.