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Datasets - hybrid training

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Together with company develop methodology for expanding training dataset with synthetic data. Datasets expansion will be perform with methods using synthetic data or data augumentation based on existing datasets

Version: 1.9

  • arable farming
  • horticulture
  • food processing
  • provision of datasets
  • data augmentation
  • data
  • other (including: nothing)
  • Location: in Poland
  • Offered by: PSNC, L-PIT



This service collaborates with your company to develop methodologies for expanding training datasets using synthetic data and data augmentation techniques. By leveraging algorithms capable of generating synthetic data from fragments of existing datasets, such as extending visual information beyond the edges of a photograph, this approach enriches training materials. The service includes creating synthetic replicas based on physical data, blending physical and synthetic data, and constructing digital terrain maps from ground truth data which can be further enhanced with synthetically generated details. Such expansion not only increases the volume and diversity of data samples but also enhances the generalization ability of AI models, offering a comprehensive solution for more robust dataset development.