Deepva face evaluation api

Face evaluation

Function description

Quality evaluation of user data

Building your own AI models for face recognition with DeepVA is an intuitive process and does not require any machine learning expertise. However, it is possible that the data provided by the user may limit the recognition performance of the AI model because it does not meet certain quality standards in terms of resolution, relative size or position. Face Evaluation analyses entire data sets and provides feedback to the user about the quality of their training data.

DeepVA Face evaluation Api


Transforming data into value

Individual person identification

Feedback on data quality without AI expertise

Anyone can build their own AI models

use cases

Face evaluation use cases

Face evaluation checks the quality of the training data. This means that all training data is checked for usability in a separate AI model: For example, if people are wearing masks or the images are too blurry, this data is recognised and cleaned up. This improves the quality of the dataset and makes face recognition more accurate and reliable.

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