Train an object-recognition AI algorithm to help Philips detect diseases faster and more accurately

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Philips case

To get to know Philips a little better, you will be provided with multiple images of Philips products. We then want you to create and train an algorithm that can recognize these Philips products from just a picture.

At Philips, we use this kind of technology to recognize and classify medical data, to help doctors detect diseases faster and more accurately. So imagine, your solution can help improve lives. But, there’s a catch! The dataset is very small (around 4 products with just 20 pictures per product). So, your algorithm will have to be trained from a small dataset. We’ll then look at the accuracy of your classifications. Best accuracy wins!

Recommended background and tools

In order to solve this, you should have a background in software engineering and an affinity with AI. You can choose any language, but we recommend python in combination with tensorflow. You should also be able to work with git and docker images to provide the deliverable.

Are you ready to take on this challenge?

Go for it! We’re really looking forward to your ideas. Sign up here and unlock all information needed to complete this case. Please note, this challenge is for all tech talents and professionals currently living in Europe (regardless of your nationality).

Philips is a leading health technology company, focused on improving people’s health and enabling better outcomes, from healthy living and prevention to diagnosis, treatment, and home care. We’re a leader in diagnostic imaging, image-guided therapy, patient monitoring, and health informatics, as well as consumer and home health.

We’re a substantial employer of technical and software roles in the Eindhoven area, across projects from clinical application development to AI, and we’d love to hear from curious and talented people with an affinity for the latest technologies.

More information about Philips:

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