  With the rise of focus on man made changes to our planet and wildlife
therein, more and more emphasis is put on sustainable and responsible gathering
of resources. In an effort to preserve maritime wildlife the Norwegian
government has decided that it is necessary to create an overview over the
presence and abundance of various species of wildlife in the Norwegian fjords
and oceans. In this paper we apply and analyze an object detection scheme that
detects fish in camera images. The data is sampled from a submerged data
station at Fulehuk in Norway. We implement You Only Look Once (YOLO) version 3
and create a dataset consisting of 99,961 images with a mAP of $\sim 0.88$. We
also investigate intermediate results within YOLO, gaining insight into how it
performs object detection.
