Automation Equipment

Deep Learning Vision

Acquire Automation is one of a select number of qualified machine vision firms utilizing deep-learning vision processing software to solve difficult applications.

Deep Learning is the future of automation equipment. In the field of automation, machines are becoming exponentially better at analyzing huge amounts of data. This intelligence allows machines to analyze the data they come across independently and to extract patterns from this data. Acquire’s Deep Learning Vision equipment mimics and even performs beyond the human eye to gather and sort the data into distinguishable forms, allowing computers to see objects and actually understand what they are. Incredible advances in the area of Deep Learning also provide an opportunity to analyze and archive massive amounts of data.

Imagine a human examining or counting a product in a production environment. The product is introduced and shown to the human, and the quality department provides numerous examples of “good” and “bad” products. The human is then tasked with manually inspecting or counting the products and trains others to do the same. If the general shape, size, and coloration are in line with what the human feels is “good”, then the product can continue for further processing. If not, the human might remove or energize an automatic removal device.

Acquire provides a true deep learning (think facial recognition) package that learns like a human. The final result is a system that can interpret and calculate similarly but never gets tired or distracted, checks a cell phone, or has to physically handle the product in order to make a decision. The advancements in this area have come far enough that the software is now affordable and can provide enormous benefits to an organization.

Acquire is truly on the cutting edge of this technology, and we can provide very detailed examples upon request.

If you need a Deep Learning Vision equipment specialist, contact us here or call (317) 849-3350 today for a free, no-obligation impact assessment.