Deep learning requires large, accurately labeled and well-balanced datasets to train AI models efficiently. Lack of datasets makes it necessary to collect and label data on one's own. However, in the case of a rare problem in reality, there is no source for acquiring real data.
We introduce a new procedure of data augmentation - an intelligent algorithm for generating synthetic data based on intelligent image blending allows you to obtain any amount of data of the highest quality.
Synthetic data can be used, among others, in the medical industry, drones, automotive, manufacturing or military industries.
Examples of the use of synthetic data in medicine:
BioCam is a company established in May 2019 and based in Wrocław, Poland. We popularize patient-friendly examination of the whole gastrointestinal tract using our own capsule endoscopy platform, based on AI technology. We believe that with our solution, capsule endoscopy will be a go-to examination of the whole gastrointestinal tract.
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