Two years ago, a powerful new computational technique called deep learning took the
field of machine vision by storm.
To improve efficiency and productivity, while remaining competitive, many companies now rely on the
power of machine vision.
The
combination of Machine Vision's camera and software to monitor all elements of packaging means products are rejected in - line unless they are 100 % shelf - ready.
But the good news is, you can discover, like Chris Dips, that the
cost of a machine vision system is a fraction of your potential yearly recall expenses.
Defended a
developer of machine vision and artificial intelligence software against claims of patent infringement in the U.S. District Court for the District of Massachusetts.
The use
of machine vision promises more reliable automobiles on the roads — with every single component within the vehicle being tested for quality at every stage of production, the amount of defective vehicles on the roads will definitely decline drastically.
Advances such as laser triangulation and CCD cameras all play a part in elevating the
status of machine visions from merely «plausible» to «effective».
The
rise of machine vision in the automotive industry have made assembly lines safer and more efficient — the removal human contact from potentially hazardous steps in the assembly line and of time - intensive quality checks done by humans have contributed to these two improvements.
However, this technology was still immature; being prone to errors, having exorbitantly high prices and the hassle that comes with
installation of machine vision into production lines all deterred potential customers from purchasing this product.
Burke's team used a machine learning technique called a convolutional neural network, which has revolutionized the
field of machine vision.
The
use of machine vision has been implemented in many industries, and it's now slowly, but surely, being integrated into one of the most mature production lines: automobile assembly lines.