Machine Vision Training Courses

Machine Vision Training Courses

Local, instructorled live Machine Vision (MV) training courses demonstrate through interactive discussion and handson practice the fundamentals and applications of Machine Vision

Machine Vision training is available as "onsite live training" or "remote live training" Onsite live training can be carried out locally on customer premises in Norge or in NobleProg corporate training centers in Norge Remote live training is carried out by way of an interactive, remote desktop

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Machine Vision Kursplaner

Tittel
Varighet
Oversikt
Tittel
Varighet
Oversikt
14 timer
Oversikt
Marvin is an extensible, cross-platform, open-source image and video processing framework developed in Java. Developers can use Marvin to manipulate images, extract features from images for classification tasks, generate figures algorithmically, process video file datasets, and set up unit test automation.

Some of Marvin's video applications include filtering, augmented reality, object tracking and motion detection.

In this instructor-led, live course participants will learn the principles of image and video analysis and utilize the Marvin Framework and its image processing algorithms to construct their own application.

Format of the Course

- The basic principles of image analysis, video analysis and the Marvin Framework are first introduced. Students are given project-based tasks which allow them to practice the concepts learned. By the end of the class, participants will have developed their own application using the Marvin Framework and libraries.
28 timer
Oversikt
OpenCV (Open Source Computer Vision Library: http://opencv.org) er et åpen kildekode-BSD-lisensiert bibliotek som inkluderer flere hundre datamaskinvisjonsalgoritmer.

Publikum

Dette kurset er rettet mot ingeniører og arkitekter som søker å benytte seg av OpenCV til prosjekter med datasyn
14 timer
Oversikt
Pattern Matching er en teknikk som brukes til å finne spesifiserte mønstre i et bilde. Det kan brukes til å bestemme eksistensen av spesifiserte egenskaper i et tatt bilde, for eksempel den forventede etiketten på et mangelfullt produkt på en fabrikklinje eller de spesifiserte dimensjonene til en komponent. Det er forskjellig fra " Pattern Recognition " (som gjenkjenner generelle mønstre basert på større samlinger av relaterte prøver) ved at den spesifikt dikterer hva vi leter etter, for så å fortelle oss om det forventede mønsteret eksisterer eller ikke.

Kursets format

- Dette kurset introduserer tilnærminger, teknologier og algoritmer som brukes i feltet mønster matching som det gjelder Machine Vision .
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