Online or onsite, instructor-led live Image Analysis training courses in Hasselt.
Hasselt
Holiday Inn Hasselt, Kattegatstraat 1, Hasselt, Belgium, 3500 Hasselt
Holiday Inn Hasselt's 5 modern meeting rooms can accommodate up to 250 delegates. All meeting rooms have natural daylight. Fr...
Holiday Inn Hasselt's 5 modern meeting rooms can accommodate up to 250 delegates. All meeting rooms have natural daylight. Free wireless internet throughout the hotel. Welcome coffee and coffee breaks will be served in our lobby by our friendly staff.
City center hotel, next to the harbour!
Modern Hasselt hotel offers free WiFi, a brasserie, and a mini gym
Holiday Inn® Hasselt places you close to the city's central bars and restaurants. A 10-minute walk away, Hasselt station is served by local and regional trains. Hotel guests enjoy on-site parking discounts. Brussels Airport is a 50-minute drive away and Liège Airport is just 35 minutes away.
Around the corner from the hotel, Modemuseum Hasselt traces the history of fashion with collections from the 18th century to the present. Five minutes away, the Jenevermuseum examines jenever, Belgium's juniper-flavoured national liquor. Stroll past cherry trees and koi ponds in the Japanese Garden, a 20-minute walk from the hotel. Opposite the park, the Trixxo Arena hosts international concert and event programmes.
Here for work? Host up to 250 delegates in the hotel's five naturally lit meeting rooms. Catering is available upon request and there's free WiFi throughout the hotel.
Enjoy city or canal views from the stylish guestrooms of this welcoming hotel where kids stay and eat free. Start your day with a buffet breakfast in the hotel's modern Brasserie De Boulevard, and enjoy our traditional Belgian cuisine. Unwind with a mini gym workout or a sauna session before meeting friends for drinks at the bar.
Pattern Matching is a technique used to locate specified patterns within an image. It can be used to determine the existence of specified characteristics within a captured image, for example the expected label on a defective product in a factory line or the specified dimensions of a component. It is different from "Pattern Recognition" (which recognizes general patterns based on larger collections of related samples) in that it specifically dictates what we are looking for, then tells us whether the expected pattern exists or not.
Format of the Course
This course introduces the approaches, technologies and algorithms used in the field of pattern matching as it applies to Machine Vision.
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.
Scilab is a well-developed, free, and open-source high-level language for scientific data manipulation. Used for statistics, graphics and animation, simulation, signal processing, physics, optimization, and more, its central data structure is the matrix, simplifying many types of problems compared to alternatives such as FORTRAN and C derivatives. It is compatible with languages such as C, Java, and Python, making it suitable as for use as a supplement to existing systems.
In this instructor-led training, participants will learn the advantages of Scilab compared to alternatives like Matlab, the basics of the Scilab syntax as well as some advanced functions, and interface with other widely used languages, depending on demand. The course will conclude with a brief project focusing on image processing.
By the end of this training, participants will have a grasp of the basic functions and some advanced functions of Scilab, and have the resources to continue expanding their knowledge.
Audience
Data scientists and engineers, especially with interest in image processing and facial recognition
Format of the course
Part lecture, part discussion, exercises and intensive hands-on practice, with a final project
PaddlePaddle (PArallel Distributed Deep LEarning) is a scalable deep learning platform developed by Baidu.
In this instructor-led, live training, participants will learn how to use PaddlePaddle to enable deep learning in their product and service applications.
By the end of this training, participants will be able to:
Set up and configure PaddlePaddle
Set up a Convolutional Neural Network (CNN) for image recognition and object detection
Set up a Recurrent Neural Network (RNN) for sentiment analysis
Set up deep learning on recommendation systems to help users find answers
Predict click-through rates (CTR), classify large-scale image sets, perform optical character recognition(OCR), rank searches, detect computer viruses, and implement a recommendation system.
Audience
Developers
Data scientists
Format of the course
Part lecture, part discussion, exercises and heavy hands-on practice
Fiji is an open-source image processing package that bundles ImageJ (an image processing program for scientific multidimensional images) and a number of plugins for scientific image analysis.
In this instructor-led, live training, participants will learn how to use the Fiji distribution and its underlying ImageJ program to create an image analysis application.
By the end of this training, participants will be able to:
Use Fiji's advanced programming features and software components to extend ImageJ
Stitch large 3d images from overlapping tiles
Automatically update a Fiji installation on startup using the integrated update system
Select from a broad selection of scripting languages to build custom image analysis solutions
Use Fiji's powerful libraries, such as ImgLib on large bioimage datasets
Deploy their application and collaborate with other scientists on similar projects
Format of the Course
Interactive lecture and discussion.
Lots of exercises and practice.
Hands-on implementation in a live-lab environment.
Course Customization Options
To request a customized training for this course, please contact us to arrange.
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Testimonials (1)
The quantity of exercises performed. Help from the trainer on each problem encountered during the exercises. He clarifies the process for us without giving the result.
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