MVTec brings deep learning to NVIDIA Pascal architecture

December 14, 2017 ECD Staff

Munich. MVTec Software GmbH has made deep learning functions available on embedded boards with NVIDIA Pascal architecture. The deep learning inference in the new version 17.12 of the HALCON machine vision software was tested on NVIDIA Jetson TX2 boards based on 64-bit Arm processors. The deep learning inference, i.e., applying the trained convolutional neural network (CNN), almost reached the speed of a conventional laptop GPU (approx. 5 milliseconds). This is possible thanks to the availability of two pre-trained networks that MVTec ships with HALCON 17.12. One of them (the so called "compact" network) is optimized for speed and therefore ideally suited for use on embedded boards. A software version for this architecture is available on request.

In addition to deep learning, the full functionality of the standard machine vision library HALCON is available on these embedded devices. Applications can be developed on a standard PC. The trained network, as well as the application, can then be transferred to the embedded device. Users can also utilize more powerful GPUs to train their CNN, and then execute the inference on the embedded system.

Previous Article
How many rubber trees are owned by the Ford Motor Company?

There is a good, albeit rather general, rule that applies to the management of a successful business: focus...

Next Article
OmniTier's CompStor Genome Assembly Software Stack Now Available

The disruptive memory-centric acceleration compute architecture delivers supercomputing assembly times with...

×

Stay updated on Developer Tools & Operating Systems with the Dev Tools and OS edition of our Embedded Daily newsletter

Subscribed! Look for 1st copy soon.
Error - something went wrong!