Quality Control for ML Training Data and Input Data

Problem

Machine Learning and Deep Learning are very popular and are nowadays applied to many fields, such as self-driving cars. However, the quality of their output largely depends on the quality of their training data but also the quality of their input data.  

Aim

Provide a systematic overview of research in the field of quality control for ML methods with a special focus on visual methods.

Contact

• Theresia Gschwandner