Blar i NTNU Open på forfatter "Aamodt, Agnar"
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Steps towards an empirically responsible AI: a methodological and theoretical framework
Svedberg, Peter O.S. (Master thesis, 2004)Initially we pursue a minimal model of a cognitive system. This in turn form the basis for the development of amethodological and theoretical framework. Two methodological requirements of the model are that explanation be ... -
Tactile-sensitive robotic grasping of food compliant objects with deep learning as a learning policy
Olofsson, Alexander Martin (Master thesis, 2017)This thesis outlines work done in generating models used to control a robotic arm and tactile sensitive gripper for successfully grasping compliant food objects, using colour and depth images as input. The compliant food ... -
Unconventional Biometrics
Barbosa, Igor Barros (Doctoral theses at NTNU;2020:262, Doctoral thesis, 2020)This thesis is a paper collection that focuses on unconventional methods of biometric recognition. Four new approaches are presented and discussed. The first two introduce and explore the concepts behind transient biometrics. ... -
Using extended siamese networks to provide decision support in aquaculture operations
Mathisen, Bjørn Magnus; Bach, Kerstin; Aamodt, Agnar (Peer reviewed; Journal article, 2021)Aquaculture as an industry is quickly expanding. As a result, new aquaculture sites are being established at more exposed locations previously deemed unfit because they are more difficult and resource demanding to safely ... -
Using similarity learning to enable decision support in aquaculture
Mathisen, Bjørn Magnus (Doctoral theses at NTNU;2021:331, Doctoral thesis, 2021)Aquaculture (AQ) is an industry that cultivates food in water. This includes many types of seafood such as salmon, trout, and whitefish, as well as shellfish and algae. Farms for seafood production are typically described ... -
Utvidelse av modell-induksjonsmetoder ved bruk av Case-Based Reasoning for forklaring av dype nevrale nett
Engen, Sondre; Perinparajan, Piraveen (Master thesis, 2019)Kunstig intelligens er i kontinuerlig utvikling i et forsøk på å løse nye og utfordrende problemer. Med AIs suksess har spørsmålet om forklarbarhet blitt tydeligere. Mange av de populære algoritmene anses å være ugjennomsiktige ...