Master topics Digital Signal Processing and 

Image analysis Group

Contact:  Anne Solberg

Convolutional networks for imbalanced classes

• Focus: study how to  improve performance of deep learning with imbalanced classes– Performance measures– Stratified  sampling– Using  alternate cost functions– Treat as anomaly detection– Other options

• Supervisor: Anne Solberg

Quantitative  QC for seismic imaging

External thesis, SchlumbergerInternal supervisor: Anne Solberg

Fault detection in seismic images

External thesis, SchlumbergerInternal supervisor: Anne Solberg

With Oliver Seynnes, NIH: Estimation and tracking of tendon

Muscle size & architecture during locomotionWith Oliver Seynnes, NIH

Example of muscle contractionThis is a scan of the vastus lateralis and vastus intermedius muscles.Typically, fascicles shorten and their curvature is altered.

VL

VI

Remote sensing: forest classification based onlidar and hyperspectral images

Unsupervised pixel classificationFalse colours display from hyperspectral image

Natural colour channels from hyperspectral image(a) Vegetation height in lidar image

In cooperation with Norsk RegnesentralMain supervisor: Anne Solberg

Typical road, aerial photo

Remote sensing: detection of cars in aerial/satellite images

Detect moving cars forpollution monitoringChallenges:- Parked cars- Shadows

Deep learning possible

In cooperation with Norsk RegnesentralMain supervisor: Anne Solberg

Satellite image, Tanzania

Remote sensing: estimating tree height from shadows Using Sentinnel-2 data (10m resolution)Remote sensing: estimating tree height from shadows Using Sentinnel-2 data (10m resolution)

Challenge: how to get robust estimatesin low resolution and noise

In cooperation with Norsk RegnesentralMain supervisor: Anne Solberg