Over the years, the manufacturing industry has been facing mounting pressure on so many fronts. They have had problems with hazardous processes that put humans in serious risks. From factories in Guangzhou, China to Grand Rapids, Wyoming, and all the way to Munich, Germany, C-level executives have been racking their brains on how to have a leap into a cleaner, safer, faster, and profitable manufacturing. How do they make the process more precise? How do they deploy automation? Until the emergence of deep learning and machine vision; a technology that has pushed the boundaries of possibilities. It is therefore important to separate the definition and the explanations around these terminologies.
Deep Learning – what exactly does it mean?
When you hear the phrase deep learning, think about large data. Deep learning machine vision software is the technology that gives machines the ability to learn from large representations of data. This means that with this technology, machines no longer (so to speak) rely on task-specific algorithms. To explain further, Deep Learning Programs rely on neural networks (software-based) to pick out the parameters they need in particular applications. In a sense, they have a childlike learning process; they do this by picking a trove of images labeled as either ‘good’ or ‘bad’.
The question then remains: what are the perfect application candidates of deep learning? These may be inspection applications where we have no pre-defined shape. This means that we are dealing with situations where object orientation or/and locations are annoyingly unpredictable. This confuses traditional machine vision applications, especially when objects do not appear the same from the camera’s perspective. In this case, deep learning will be a great alternative. Deep Learning together with machine vision will present a disruptive combination.
Deep Learning will hugely increase vision proficiency. If you are looking at deploying this new technology in your manufacturing company, please contact us.