Due to the high demand we have eight new seminar dates for 2020! In this seminars you will learn how to use deep learning in your image processing applications using the deep learning technology classification, object detection and semantic segmentation.
About MVTec Technology Days
In small groups, our experienced trainers will show HALCON users what deep learning can accomplish within your application. In order to provide a hands-on approach on deep learning each participant will be provided with his own laptop and camera setup.
Deep Learning 1
With the help of the deep learning technology classification, you will learn how to use deep learning in your image processing applications:
- Introduction to HALCON-specific basics regarding deep learning
- Background knowledge about deep learning in industrial machine vision applications
- Best practices for setting up one's own deep learning applications
- "Hands-on" approach: programming a deep learning image classification application
- Analysis of a deep learning image classification
Deep Learning 2
With the deep learning technology object detection and semantic segmentation you will learn how to use deep learning in your image processing applications.
Based on MVTec Technology Day - Deep Learning 1, learn more about how to use the deep learning technologies object detection and semantic segmentation:
- Introduction to the MVTec Deep Learning Tool
- Introduction and best practices for the deep learning technologies object detection and semantic segmentation
- "Hands-on" approach to a deep learning problem for object detection – from labeling to inference
- Choosing the right deep learning method for your own application
|Deep Learning 1||Deep Learning 2|
July 7, 2020
|July 8, 2020|
September 30, 2020
November 25, 2020
|Time||10 a.m. to 5:45 p.m.||9 a.m. to 5 p.m.|
|Fee||790,00 € plus 19 % VAT||790,00 € plus 19 % VAT|
|Target group||HALCON users|
notebook for the day
camera setup for practical
use in the seminar
Please note that seats are limited ("first come - first serve").
Each seminar is a stand-alone seminar and can be booked separately. However, to gain most of this seminar, we recommend to visit the introductory seminar Deep Learning 1 first.