Abstract

The aim of this study is to the investigate how machine learning can be implemented to improve inter-model agreement between two spectrophotometers. Models within supervised learning are used and evaluated with colorimetric metrics. The work is conducted at NCS Colour AB, a Stockholm based company that works with colour communication and colour quality.