Identification of bagged lamb racks using machine learning algorithms

AMPC partnered with MEQ Probe to develop a suite of algorithms, software, and machine learning models to identify bagged lamb primals on a red meat processing plant conveyor belt at chain speed. 

As part of the project, 30,000 images of bagged lamb racks were collected and used for model training and analysis. Once these images were captured and labelled, a machine learning model was developed, and an algorithm was trialed to recognise bagged lamb rack primals in images. 

The machine learning model was used on a boning belt with 100 per cent accuracy at chain speed.