Deep Learning Extends the Power of Machine Vision
Artificial intelligence and specifically deep learning is getting more and more powerful. Deep learning solutions can serve very specific requirements.
In machine vision, deep learning enables an increasing number of applications that weren’t possible before. Moreover, the performance of existing applications can be significantly improved. Especially in the field of data classification, deep learning is a very efficient technology. Many industries and sectors are already benefiting from the new opportunities, such as agriculture, mechanical engineering, pharmaceuticals, logistics, etc.
MVTec software products offer a large selection of operators, functions and methods that either are based on deep learning technologies or allow customers to use deep learning technologies in their own applications.
Learn more about deep learning methods, the differences to classic machine vision and how to start with deep learning.
Application Examples
Logistics
Whether you need to classify packages or control an unmanned pallet truck, deep learning solutions enable you to solve machine vision tasks faster and more cost-effectively.
Example: Identification of empty rack spaces
The implemented deep-learning-based solution works with 2D image data, replacing a complex hardware setup with 3D sensors. This accelerated the classification process and reduced costs.
Agriculture & Food
From classifying fruits, feeding animals, picking ripe vegetables, packing fruits in bags, or producing frozen goods – deep learning technologies will enhance your automation, whether in the greenhouse, in the field, in the barn, or in the production plant.
Example: Identification of plants
With deep learning, new plant types could be programmed twice as fast as before. Moreover, the error rate was significantly reduced.
Electronics & Semiconductors
Machine vision plays a big role for, e.g., the identification and inspection of electronic components. With deep learning, complex inspection tasks that were previously performed manually can be automated.
Example: Quality check of circuit board printing
The classification of good and bad images of different circuit board parts could be significantly accelerated with deep learning.
Medical & Pharma
If you are looking for a tool that takes your quality control to the next level, deep learning technologies are the right choice. Whether you need to detect defects on pills, sort tablets correctly, fill, inspect or package bottles or labels – machine vision with deep learning improves your processes.
Example: Detection of defects on pills
New types of defects could be trained automatically, which means enormous time and costs savings.