Msc-studenter

Ferdige masterstudenter de seneste årene:

 

Johanne Saxegaard (2022): Deep learning-based segmentation of brain metastases on multi-centre MR data T

Aram Salihi (2022): The usage of 2.5D UNet architectures and different preprocessing techniques for segmentation of multiple sclerosis

Fabian Bull (2021): Introducing an efficient approach for expressing uncertainty in deep learning

Martin Røvang (2021): Segmentation of white matter hyperintensities in magnetic resonance images

Mona Heggen (2021): An investigation of different interpretability methods used to evaluate a prediction from a CNN model

Andreas Bergem (2019): Detection and Tracking of Fish in Underwater Video (hovedveileder Jørn Bersvendsen)

Ole-Christian Schmidst Hagenes (2019): Comparison of structure tensors for direction and motion estimation in medical ultrasound (hovedveileder Sten Roar Snare, GE Vingmed)

Peter Ivarsen (2019): Visual Inertial Direct SLAM (hovedveileder Trym Haavardsholm, FFI)

Nirusan Thamaranthan (2019): Using time information to make a robust feature extraction and parameter estimation from unipennate muscles in B-mode ultrasound sequences

 

Sissel Fladby (2017): Automatic feature extraction and parameter estimation from unipennate muscles in B-mode ultrasound images (med Olivier Seynnes, NIH)

Johan Myre (2017): Autonom rørdeteksjon på havbunnen - Deteksjon av rørledninger i data fra multistråle-ekkolodd (med Øivind Midtgaard, FFI)

Frida Jalborg (2016): Automatic detection of skeletar muscle parameters  (med Olivier Seynnes, NIH)

Ragnar Smestad (2014): Automatisk deteksjon av menneskeskapte objekter med optisk kamera fra autonome undervannsfarkoster  (Hovedveileder Øivind Midtgaard, FFI)

Erik Solfjell (2013): Integrasjon av AIS-data i deteksjon av oljesøl i SAR-bilder

Gjermund Stensrud (2013):  Automatic segmentation of mine-like objects in synthetic aperture sonar images

Rebekka Mørken Valdmanis (2013): Computation of curvature in seismic data

 

 

 

 

Publisert 16. aug. 2019 11:30 - Sist endret 16. okt. 2023 11:17