16 citations · 23 across the 2 of their papers we have counts for
7 papers
Instance Segmentation of Microscopic Foraminifera
Thomas Haugland Johansen, Steffen Aagaard Sørensen, Kajsa Møllersen +1
Foraminifera are single-celled marine organisms that construct shells that remain as fossils in the marine sediments. Classifying and counting these fossils are important in e.g. p…
Soft thresholding schemes for multiple signal classification algorithm
Sebastian Acuña, Ida S. Opstad, Fred Godtliebsen +2
Multiple signal classification algorithm (MUSICAL) exploits temporal fluctuations in fluorescence intensity to perform super-resolution microscopy by computing the value of a super…
Data-Driven Robust Control Using Reinforcement Learning
Phuong D. Ngo, Fred Godtliebsen
This paper proposes a robust control design method using reinforcement-learning for controlling partially-unknown dynamical systems under uncertain conditions. The method extends t…
A bag-to-class divergence approach to multiple-instance learning
Kajsa Møllersen, Jon Yngve Hardeberg, Fred Godtliebsen
In multi-instance (MI) learning, each object (bag) consists of multiple feature vectors (instances), and is most commonly regarded as a set of points in a multidimensional space. A…
Comparison of computer systems and ranking criteria for automatic melanoma detection in dermoscopic images
Kajsa Møllersen, Maciel Zortea, Thomas R. Schopf +2
Melanoma is the deadliest form of skin cancer. Computer systems can assist in melanoma detection, but are not widespread in clinical practice. In 2016, an open challenge in classif…
On Data-Independent Properties for Density-Based Dissimilarity Measures in Hybrid Clustering
Kajsa Møllersen, Subhra S. Dhar, Fred Godtliebsen
Hybrid clustering combines partitional and hierarchical clustering for computational effectiveness and versatility in cluster shape. In such clustering, a dissimilarity measure pla…