🧠 Machine Learning

The application of AI and other news from our Research Team

How we use machine learning and computer vision to recommend products

Our Head of Research Ilaria looks at how we're using machine learning and computer vision to make consumers' lives easier when it comes to picking bathroom furniture. Jump in below to find out more.

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How our AI Auto-Design uses Genetic Algorithms

One of the blockers when renovating a bathroom is deciding where products should go and what size they should be for the consumer to use them effectively. Do you like free-standing baths but your bathroom is too small? Do you have a downstairs toilet but you’re struggling to fit a basin? We’re here to help with our AI Auto-Design technology.

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How we use Machine learning at DigitalBridge

It’s difficult to renovate a bathroom. There are a thousand things to do, all of which a typical customer has never done before. This problem is compounded by the imagination gap. When a customer views a product, it can be difficult for them to picture how that product will look in their bathroom. Is there a good place for that product? Is the product an appropriate size for the room? What does it look like in that space? These questions, and questions like these, are difficult to answer for a novice bathroom designer.

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My thoughts on ECML PKDD 2018

David, a member of our research team, jetted over to Dublin for ECML PKDD 2018. In this blog post he talks about the elements of the conference he found most interesting.

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Deep Depth Prediction - The Next Revolution?

Ever wondered how a phone might understand what a room looks like if everything looks exactly the same? Computer Vision Researcher Ignazio explains.

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5 techniques for generating 3D information and when to use them

In this post, Mohamed gives an overview of the most commonly used techniques to acquire 3D information, briefly illustrates the theory behind them and highlights their strengths and weaknesses.

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3 reasons we’re excited about Google’s ML Kit

Last week, at their annual I/O developer conference in California, Google unveiled ML Kit. This new software will accelerate our ability to embed machine learning models into our apps and allow us to experiment with models to create proof of concepts very quickly.

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4 things I learned at KDD 2018

Our Head of Research Ilaria headed to KDD 2018 to spot new trends in machine learning. Find out what she learnt below.

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Can we use stereo vision with ARKit to estimate floor plans?

Our Research Team take a look behind the scenes at how your phone can be used to scan a room and create an accurate floor plan.

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How we use image semantic segmentation

At DigitalBridge we create products that aid the design and visualisation of kitchens, bedrooms and bathrooms. Using sophisticated computer vision algorithms we allow a user to design and visualise their new kitchen, bedroom or bathroom in their existing room. By understanding the user’s current space we can make informed decisions on how to assist them in this process.Scene understanding is the process of using a photo (or set of photos) to return semantic knowledge of a scene’s contents. One aspect of scene understanding is determining the objects in a photo. This may be performed at the object level, through object detection, or at the pixel level through semantic segmentation. This blog post will focus on the latter.

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