MVTec Software GmbH (www.mvtec.com), the leading provider of innovative machine vision software, invites guests to attend MVTec Innovation Day once again this year. On Thursday, February 20, 2020, visitors will gain practical insight into the latest machine vision topics at Haus der Bayerischen Wirtschaft in Munich. Aimed especially at developers, programmers, and experienced machine vision users, MVTec experts will illustrate trends, technologies, and solutions in a variety of presentations. The MVTec team will also be on hand for a direct exchange and technical discussions. During the breaks and evening event, attendees will have the opportunity to visit an exhibition with live demonstrations as well as network with colleagues in a relaxed atmosphere. The event will take place in German, with professional simultaneous interpreters available for all non-German speakers.
Expert presentations on the latest trends and technologies
The presentations will focus on the latest trends and technologies as well as their application in daily practice. One of these is the efficient anomaly detection in deep-learning-based inspection tasks using the standard machine vision software MVTec HALCON. Other topics to be presented are deep-learning-based optical character recognition (OCR), examples of the latest embedded vision applications, HALCON's generic box finder for pick-and-place applications, and identification via subpixel bar code reader. The experts will also discuss general market developments and future milestones at MVTec. Moreover, visitors will receive valuable tips from MVTec developers and can enter a drawing to win for example a license for MVTec’s software products or a deep-learning training course. For the first time, this year's Innovation Day will also feature external speakers – for example, from B&R and Manz AG – who will discuss topics like embedded vision and deep learning.
Throughout the day, fascinating live demonstrations will provide practical insights into the use of modern machine vision applications in industrial environments – with an emphasis on scenarios that focus on embedded vision and deep learning.
