Computer Vision & Data Science
Computer Vision is a technological field in which the goal is to automatically extract information from images. For example: disease detection in crops, wind turbine blade inspection using smart civil drones and chemical fingerprinting of polymers using specialized cameras. Computer Vision research is multidisciplinary and combined with Data Science and Parallel Computing to solving complex image analysis tasks.
In the Centre of Expertise in Computer Vision and Data Science you can follow a minor, do an internship or do your graduation project. During your minor or internship you will be working together with an experienced team of engineers, researchers and professors (of applied sciences) on challenging state-of-the-art applied research projects in the area of Computer Vision and Data Science. You learn to develop innovative applications of Computer Vision & Data Science.
Computer Vision mainly revolves around obtaining and processing raw sensor data (images) to information (measurements in pictures) and eventually to knowledge (research). At Computer Vision, the focus is image acquisition and image processing, at Data Science, the focus is recognizing patterns in that information (Big Data) with the help of, among others, Deep Learning. As student in our research lab you have access to state-of-the-art equipment like a mini super-computer, 3D cameras, high speed cameras, hyper- and multispectral cameras, surround cameras, industrial cameras, many types of optics, lighting, and unmanned aerial vehicles (drones).
On our website you will find more information about our group and the projects we are working on https://www.nhlcomputervision.nl/.
At the end of the minor or internship you can design, develop, and research a Computer Vision and Data Science application. You will get familiar with the following aspects:
- Image acquisition and configuration of a vision system (camera, lens and illumination)
- Image segmentation, image classification, object detection or object counting using deep learning and computer vision.
- Validation and optimization of algorithmic performance on datasets.
- Programming and using libraries and software tools.
- Applied research methodology and writing a technical paper.
- Project management using SCRUM.
- Design Based Education in short prototyping cycles.
You study with us full-time for the length of a semester, you can start each semester (Sept or Feb).
For more information and contact information check our website http://www.nhlcomputervision.nl/students/.
If you like more information, please feel free to contact us, you will find us in G2.016 (Rengerslaan 10 in Leeuwarden) and can reach us by mail email@example.com.
Technical propedeutic diploma and affinity with programming, engineering and applied research.
Are you interested in participating in our research lab as a minor student? Then please, send in a motivation letter with CV, both in English. You should view this as a job application. In your letter you mention your learning goals and what attracts you in our group. Based on your letter, we will check whether there is a match between your learning objectives and what we can offer. Note, there is a maximum number of places available per semester. Admission is based on suitability and orderliness. It is therefore important to express your interest in time.
Technical paper, poster, presentation and a demonstrator/proof of concept.
The semester starts with a compulsory kick-off course on Computer Vision & Data Science. During this course the basics are explained. After this, projects are awarded to the students based on personal interests and technical background. For the remainder of the semester you will, in a group or individually, work on an real-life applied research projects from one of our partner companies. Progress is discussed in weekly SCRUM meetings and there is ample opportunity to ask questions. Students and staff work in two adjacent rooms. We are a small and flexible team and communication lines are short. In monthly sprints you work towards an end product, consisting of a technical paper, poster, presentation and a demonstrator/proof of concept.