Internship | Deep learning models for real-time small object detection
About this position
The Intelligent Imaging group at TNO is researching and developing methods to increase situational awareness of operators and robots in many areas by leveraging state-of-the-art (SOTA) deep learning imaging technologies. Situational awareness of large areas implies that objects appear small in the image, can be occluded, and still need to be detected in all weather conditions. One important aspect is to detect relevant objects with high precision and high confidence in real time with low latency.
What will be your role?
Small objects don't have many pixels. This means that there are almost no disguisable features, which makes it hard to distinguish them from each other, even for humans! This can lead to many false positives which are not desirable for robots and operators. Other challenges are the absence of training data. Currently, there is a lack of (open-source) datasets for tiny objects, our objects of interest, and our viewpoints. This makes it hard to train (video) object detectors for these situations. Furthermore, deploying such SOTA deep learning models on Size Weight and Power (SWAP) restricted embedded systems is a challenge while real-time inference on high-resolution images/video also poses an extra challenge due to the limited processing resources.
Your research will aim to improve this deep-learning-based small (real-time) object detection in one of its many challenges. We are flexible in the assignment, and you are able to choose one of the challenges depending on your interest or come up with your own challenges in this area. With your work, you will contribute to real-world applications as well. The improvements in small (real-time) object detection are very important for Search and Rescue applications, for example in drowning detection from a drone at the sea cost where we are currently working on: https://nos.nl/video/2384218-drenkelingen-sneller-ontdekt-met-speciale-drone-van-knrm
You will perform this assignment at TNO's Intelligent Imaging department. The Intelligent Imaging group is specialized in image processing, image enhancement, image analysis, visual pattern recognition, artificial intelligence and deep learning. This young, passionate, creative and committed group (50 people) works with partners on technological breakthroughs for innovations in important societal and economic themes, developing knowledge in various research areas including both AI (e.g. learning with less data or hybrid AI) as well as crucial non-AI knowledge, real-time algorithms, edge processing and information fusion.
What we expect from you
You are in the final stages of your master’s degree in artificial intelligence, computer science, mathematics, electrical engineering, robotics, systems and control engineering, physics or a similar degree. You have some experience in computer vision, artificial intelligence and deep learning, and programming in Python. Next to technical expertise, we value communication skills, a results-driven attitude, and that you are motivated to publish your work.
The project is for a period of 6 to 12 months, during which you will have the ability to work from home as well as our office and you will receive an appropriate internship fee. Please mention in your application whether you are looking for a graduation project or an internship, your preferred start date and your preferred duration of the project.
Keywords here are: Deep Learning, Machine Learning, AI, Computer Vision, Image Classification, Object Detection, Object Segmentation, Video Object detection, Tracking PyTorch, Pytorchlightning, Tensorflow, Keras.
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. Read more about TNO as an employer.
At TNO we encourage an inclusive work environment, where you can be yourself. Whatever your story and whatever unique qualities you bring to the table. It is by combining our unique strengths and perspectives that we are able to develop innovations that make a real difference in society. Want to know more? Read what steps we are taking in the area of diversity and inclusion.
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.
For this internship vacancy it is required that the AIVD issues a security clearance (VGB) after conducting a security screening. Take into account that this process may take about 8 weeks. If you have been abroad for more than 6 consecutive months, or if you do not have the Dutch nationality, it may take longer. Read more about security screening on the AIVD website.
Has this job opening sparked your 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.