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Intelligent Digital Inspectors

BrainCreators delivers intelligent digital inspectors that automate visual inspection tasks.

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Surface Inspectors

A Digital Surface Quality Inspector
A Digital Road Surface Inspector
A Digital Radar Image Inspector
A Digital Inspector for quality control
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Object Inspectors

A Conveyor Belt Item Inspector
A Digital Apparel Inspector
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Spatial Inspectors

A GDPR compliant crowd inspector
A Digital Airport Asset Inspector
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About us

BrainCreators' Digital Inspectors are like super-powered employees who are trained on our BrainMatter platform so you can scale your business more Effectively & Cost Efficiently.

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Intelligence Digital Inspectors
powered by Artificial Intelligence

Our clients and partners in various industries transfer their expert knowledge and skill to the BrainMatter platform to develop scalable Digital Inspectors.

BY INDUSTRY

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Visual inspection of physical and organizational structures and facilities
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Visual inspection of goods on large scale production lines
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Visual inspection of indoor and outdoor places & spaces
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Visual inspection for products, stores, and warehouses
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Visual inspection in smart cities, public transport and event spaces
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Visual inspection of pipes, cables, and power lines

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Resources

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AI in practice

A knowledge hub for everything related to digital inspectors and the AI that powers them

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Available eBooks

Employing intelligent automation for better business operations
Digital Inspectors accelerate workflows at lower costs.
How to use Artificial Intelligence (AI) without a degree in data science

The 7 habits of highly effective asset management
3 Successful Business Cases in Infrastructure
Revolutions in civil infrastructure management

BrainCreators create more efficient AI systems for understanding video data

Researchers of the Dutch company BrainCreators and the University of Amsterdam have developed a new machine learning method for understanding human actions in video data. Its main contribution is in the efficiënt use of expensive AI training data. 

The new technique is called Video Cross-Stream Prototypical Contrasting (ViCC) and is ideally suited for automatically recognizing human action in video, efficiently searching through large amounts of data and intercepting anomalous data. This can be done with limited support from people or even without any intervention at all.

In a paper titled Self-supervised Video Representation Learning with Cross-Stream Prototypical Contrasting, the scientists describe how artificial intelligence can extract more information from the videos combining color information and the flow of movement.

The field of Self-Supervised AI attempts to solve the biggest bottleneck in current machine learning applications: the dependency on expensive, human annotated data. While many methods exist, the prime contribution of ViCC is a novel way to learn from data by comparing images with each other, instead of with their human given labels. Combined with a smart way to group raw data samples together, this leads to new state-of-the-art performance. While the improvement in speed is modest, the action recognition results are much better. 

According to the researchers, ViCC can be applied in existing visual recognition models, such as BrainCreators’ digital inspectors - Ara and Inspech. Read the full dutch article here

Authors: Martine Toering, Ioannis Gatopoulos,  Maarten Stol en Vincent Tao Hu

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