Keywords:
Artificial Intelligence
Type:
Internship
Location:
Den Haag
Education:
Bachelor (EQF 6), Master (EQF 7)
Published:
27/10/2021
Status:
Open
Apply before:
31/12/2021
Hours p/wk:
40
More information

Description:

Internship - Small object detection for surveillance and search and rescue

In defence and security applications there is a growing demand for automatic surveillance of large areas. At TNO we are developing methods to increase situational awareness of defence and security operators. The Intelligent Imaging group focuses on leveraging the benefits of cameras and image sensors to reach this goal.

 

What will be your role?

With the recent advances in deep learning, it becomes possible to analyse images or videos to automatically detect objects of interest. The speed and effectiveness of finding relevant objects, such as vehicles or persons, in a large area is significantly affected by the amount of pixels covering this object. Surveillance of large areas implies that objects appear small in the image. The quality of the detection of such small objects is often poor when using generic object detectors trained on standard public datasets. The Intelligent Imaging group focuses on leveraging new technologies, such as image processing and deep learning methods.

You will research new techniques to push the limits of small object detection, which includes:

  • making an overview of various solutions and algorithms for small object detection
  • making a selection of the most relevant solutions and algorithms
  • investigating potential benefits in directions, for example: applying model ensembles, using temporal information, using spatial information (e.g. image context around object), selecting and composing specific datasets for training.
  • designing, implementing and evaluating proposals for improving the performance of small object detection solutions.

What we expect from you?

You are in your final stages of a master’s degree in artificial intelligence, computer science, physics, mathematics, electrical engineering, or a similar degree, preferably have some track record in deep learning, computer vision or image processing. A solid background in programming (Python) is necessary.

 

What you'll get in return

You want to work on the precursor of your career; a work placement gives you an opportunity to take a good look at your prospective future employer. TNO goes a step further. It’s not just looking that interests us; you and your knowledge are essential to our innovation. That’s why we attach a great deal of value to your personal and professional development. You will, of course, be properly supervised during your work placement and be given the scope for you to get the best out of yourself. Naturally, we provide suitable work placement compensation.

 

TNO as an employer

At TNO, we innovate for a healthier, safer and more sustainable life. And for a strong economy. Since 1932, we have been making knowledge and technology available for the common good. We find each other in wonder and ingenuity. We are driven to push boundaries. There is all the space and support for your talent and ambition. You work with people who will challenge you: who inspire you and want to learn from you. Our state-of-the-art facilities are there to realize your vision. What you do at TNO matters: impact makes the difference. Because with every innovation you contribute to tomorrow’s world. 

 

The selection process

After the first CV selection, the application process will be conducted by the concerning department. TNO will provide a suitable internship agreement. If you have any questions about this vacancy, you can contact the contact person mentioned below.

Due to Covid-19 and the consequent uncertainties and restrictions, students who are not residing in the Netherlands may currently not be able to start an internship or graduation project at TNO.

 

Has this job sparked an interest?

Then we’d like to hear from you! Please contact us for more information about the job or the selection process. To apply, please upload your CV and covering letter using the ‘apply now’ button on the website.

 

Contact: Pieter Piscaer
Phone numberpieter.piscaer@tno.nl