Testing and Integration of Machine Learning Components for Image Classification : Testning och integration av machine learning komponenter förbildklassificering

Abstract: As ML (Machine Learning) and deep neural networks get more used in many systems,the need to understand and test such systems becomes more actual. When designing a newsystem that contains ML models, the safety of this system becomes inevitably important.This rises the need to discuss a strategy to deal with the potential problems and weak-nesses in such a system. This thesis provides findings from literature and illustrates thepotential strategies in the area of image recognition in a comprehensive way. Lastly, theresult presented in this thesis shows that using an ML component in a complex softwaresystem with high safety requirements requires adopting software methodologies, such asMLOps (Machine learning operations) to monitor such a system and give suggestions tohow to test and verify an ML model integrated into a larger software system.