{{'Deep Learning' | translate }}


{{'It is an Artificial Intelligence tool for advanced quality control or machine diagnostics. It uses machine vision and deep neural networks. Ideal for image, video, sound, or vibration recognition. Neural networks are taught similarly to humans according to examples (patterns). Their advantage is the generalization capability, that they apply the learned knowledge to differing conditions from those under which they were taught.' | translate }}

{{'Learning' | translate }}

{{'The system learns according to the pattern that indicates the user in the web browser. Users define the types of defects which has to be detected.' | translate }}

{{'Training' | translate }}

{{'The system can be taught by adding new patterns. In the event of a new flaw, the user will only mark the new images and let the system automatically retrain. Everything is done on a user-friendly basis without programming.' | translate }}

{{'Visual quality control' | translate }}

  • {{'Detection of surface defects of materials' | translate }}
  • {{'From static images' | translate }}
  • {{'From video ' | translate }}
  • {{'Runs on a less powerful computer' | translate }}

{{'Sound quality control' | translate }}

  • {{'Classification into categories (OK, NOK)' | translate }}
  • {{'Prediction of future developments' | translate }}
  • {{'Using microphone in audible and inaudible spectrum' | translate }}