Martin Cassel

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So far Martin Cassel has created 166 blog entries.
29 11, 2018

VisualApplets Workshops in 1st Quarter

Silicon Software offers an extensive training program for you to learn the award winning VisualApplets graphical FPGA development environment in an optimal fashion. VisualApplets was developed by Silicon Software to empower software and applications engineers to use FPGA accelerated hardware based image processing in their solutions. Its graphical approach via data flow models greatly simplifies

27 11, 2018

ITE 2018 in Japan – Machine Vision with Deep Learning

At ITE 2018 (International Technical Exhibition on Image Technology and Equipment) in Yokohama (Japan) from December 5th to 7th we will present our hardware and software products for machine vision in hall D, booth 1 together with our Japanese partner LINX Corp. Focus is on Deep Learning, embedded Vision and Computational Imaging for a closer integration

19 11, 2018

Concurrent EDA Certified as VisualApplets Design Center

With Concurrent EDA we have gained a new development partner in the North American market for graphical FPGA development with VisualApplets, who will intensively support our customers and distributors. The company has been certified as a VisualApplets Design Center (VADC) for its outstanding expertise in converting specific function libraries directly

13 11, 2018

LINXDays – One of the Biggest Vision Events

The Technology Seminar LINXDays is one of the world's largest vision events in Japan, organized by our Japanese distributor LINX. From November 19 to 22, 2018, more than 1,000 participants will be expected at three locations in Japan for an extended lecture program focusing on industrial automation, which will also consider the

2 11, 2018

SPS IPC Drives 2018 – Vision, IT and Automation Meet Each Other

From November 27 to 29, the SPS IPC Drives trade fair for automation technology will take place in Nuremberg, Germany, in 17 exhibition halls, this time under the motto "Smart and Digital Automation". Digitization also stands for a stronger integration of IT systems such as image processing into industrial automation, combined with technical requirements for

18 10, 2018

VISION 2018 – Deep Learning, New Hard- and Software

At VISION 2018, booth 1C72, we will focus on CNN-based deep learning hardware and software on FPGAs for real-time applications with high bandwidths in object and feature classification. The close interaction of our hardware and software is suitable for the integration of neural networks of different depth and size for industrial requirements such as inline

15 10, 2018

CRAV Conference 2018 Combines Robotics and Vision with AI

This year's Collaborative Robots, Advanced Vision & AI Conference (CRAV.AI) held on October 24-25, 2018 in San Jose, U.S.A. presents the latest developments in robotics and vision and combines them for the first time with Artificial Intelligence (AI). Users, OEMs, manufacturers and integrators from the automation industry will find something of interest,

8 10, 2018

Webinar about „How to use FPGAs to accelerate deep learning“

While deep learning is a hot topic, it is still limited to non-manufacturing production rate speeds. To go beyond the real-time performance limit of GPUs, a new technology must be considered in combination with deep learning inference models... FPGA processors! This webcast demonstrates how Deep Learning is used as modern classification technology

2 10, 2018

New Chair of the VDMA Machine Vision Group

Our CEO, Dr. Klaus-Henning Noffz, has been elected Chairman of the VDMA Machine Vision group in the Robotics & Automation trade association for the next three years on its general meeting on September 28th and 29th. He succeeds Dr. Olaf Munkelt, Managing Director of MVTec Software GmbH, who held this position for nine years.

1 10, 2018

70th Heidelberg Image Processing Forum about Machine Learning

The 70th Heidelberg Image Processing Forum will focus on "Machine Learning and Ground Truth for Image Processing". New technologies such as deep learning raise new questions: Why are these procedures so successful? What characteristics must data sets have so that learning processes can be successfully developed with them? From a legal point of view, what