4 citations · 5 across the 7 of their papers we have counts for
4 papers · 1 filter
Segmenting Wood Rot using Computer Vision Models
Roland Kammerbauer, Thomas H. Schmitt, Tobias Bocklet
In the woodworking industry, a huge amount of effort has to be invested into the initial quality assessment of the raw material. In this study we present an AI model to detect, qua…
Machine Learning in Industrial Quality Control of Glass Bottle Prints
Maximilian Bundscherer, Thomas H. Schmitt, Tobias Bocklet
In industrial manufacturing of glass bottles, quality control of bottle prints is necessary as numerous factors can negatively affect the printing process. Even minor defects in th…
Training a Computer Vision Model for Commercial Bakeries with Primarily Synthetic Images
Thomas H. Schmitt, Maximilian Bundscherer, Tobias Bocklet
In the food industry, reprocessing returned product is a vital step to increase resource efficiency. [SBB23] presented an AI application that automates the tracking of returned bre…
Semmeldetector: Application of Machine Learning in Commercial Bakeries
Thomas H. Schmitt, Maximilian Bundscherer, Tobias Bocklet
The Semmeldetector, is a machine learning application that utilizes object detection models to detect, classify and count baked goods in images. Our application allows commercial b…