Blar i NTNU Open på forfatter "Måløy, Håkon"
-
A Dual-Stream Deep Learning Architecture for Action Recognition in Salmon from Underwater Video.
Måløy, Håkon (Master thesis, 2017)Over half of the costs from breeding salmon in the Norwegian salmon farming industry comes from feed usage. Today the feeding process is largely a manual labor, requiring an operator to monitor the amount of feed sinking ... -
A spatio-temporal recurrent network for salmon feeding action recognition from underwater videos in aquaculture
Måløy, Håkon; Aamodt, Agnar; Misimi, Ekrem (Journal article; Peer reviewed, 2019)Recent developments have shown that Deep Learning approaches are well suited for Human Action Recognition. On the other hand, the application of deep learning for action or behaviour recognition in other domains such as ... -
EchoBERT: A Transformer-Based Approach for Behavior Detection in Echograms
Måløy, Håkon (Journal article; Peer reviewed, 2020) -
FishNet: A Unified Embedding for Salmon Recognition
Mathisen, Bjørn Magnus; Bach, Kerstin; Meidell, Espen; Måløy, Håkon; Sjøblom, Edvard Schreiner (Chapter, 2020)Identifying individual salmon can be very beneficial for the aquaculture industry as it enables monitoring and analyzing fish behavior and welfare. For aquaculture researchers identifying indi- vidual salmon is imperative ... -
Learning neural representations for the processing of temporal data in deep neutral networks
Måløy, Håkon (Doctoral theses at NTNU;2023:6, Doctoral thesis, 2023)Ever since the third spring of artificial intelligence a decadeago, representation learning through deep neural networks hasbeen the dominating approach for most research in machinelearning. However, typical deep neural ... -
Multimodal performers for genomic selection and crop yield prediction
Måløy, Håkon; Windju, Susanne; Bergersen, Stein; Alsheikh, Muath K; Downing, Keith Linn (Peer reviewed; Journal article, 2021)Working towards optimal crop yields is a crucial step towards securing a stable food supply for the world. To this end, approaches to model and predict crop yields can help speed up research and reduce costs. However, crop ... -
Understanding and Visualizing Filters in Deep Convolutional Neural Network Architectures
Aunrønning, Ola (Master thesis, 2018)Deep neural networks are black boxes. While we know how they learn, we still don t have a great understanding of what they learn. This project has a goal of visualizing and understanding what convolutional neural networks ...