Detection of points on a fish for optimal cutting using deep learning
Photo: Jostein Henriksen

Detection of points on a fish for optimal cutting using deep learning

Master thesis on automation in the fish processing industry using machine learning.

Master thesis on automation in the fish processing industry using machine learning by Josten Henriksen.

Towards automation in the fish processing industry using machine learning.

Jostein Henriksen (private)

Jostein Henriksen M.Sc. student at Department of Physics and technology (IFT) is working towards using artificial intelligence in the fish processing industry. In his master thesis, Jostein is developing techniques for the automatic cutting of fish in order to improve efficiency and minimize wastage. This is a collaboration between UiT Machine Learning Group and Havfront AS – an industrial partner that provides leading solutions for automatic fish cutting and processing.

In his master thesis, Jostein is using state-of-the-art object detection models such as YOLOv7 and Detectron2 to identify the important points on a fish that are used for guiding the automatic blades in order to achieve an optimal cut. Jostein’s master thesis is supervised by Puneet Sharma from the Department of Automation & Process Engineering (IAP).

Read the Master thesis available on MUNIN HERE


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