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F. Fineide, A. Storås, M. Magnø, H. L. Hammer, X. Chen, A. Khan, P. Halvorsen, T. Utheim and M. Riegler

Predicting the degree of meibomian gland dropout with artificial intelligence

In ARVO Annual Meeting, 2023.
Proceedings, refereed
2023
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A. Storås, F. Fineide, H. L. Hammer, A. Khan, M. Magnø, C. Xiangjung, P. Halvorsen, T. Utheim and M. Riegler

Using explainable artificial intelligence (XAI) to explore factors affecting meibomian gland (MG) dropout

In ARVO Annual Meeting, 2023.
Proceedings, refereed
2023
View
H. L. Hammer, M. Riegler and H. Tjelmeland

Approximate Bayesian Inference Based on Expected Evaluation

Bayesian Analysis 1, no. 1 (2023).
Journal Article
2023
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A. Sharma, M. Stensen, E. Delbarre, M. Siddiqui, T. Haugen, M. Riegler and H. L. Hammer

Detecting human embryo cleavage stages using YOLO v5 object detection algorithm

In Nordic Artificial Intelligence Research and Development. Springer, 2023.
Proceedings, refereed
2023
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2023

Journal articles

H. L. Hammer, M. Riegler and H. Tjelmeland

Approximate Bayesian Inference Based on Expected Evaluation

Bayesian Analysis 1, no. 1 (2023).
Status: Published

Proceedings, refereed

F. Fineide, A. Storås, M. Magnø, H. L. Hammer, X. Chen, A. Khan, P. Halvorsen, T. Utheim and M. Riegler

Predicting the degree of meibomian gland dropout with artificial intelligence

In ARVO Annual Meeting, 2023.
Status: Published
A. Sharma, M. Stensen, E. Delbarre, M. Siddiqui, T. Haugen, M. Riegler and H. L. Hammer

Detecting human embryo cleavage stages using YOLO v5 object detection algorithm

In Nordic Artificial Intelligence Research and Development. Springer, 2023.
Status: Published
A. Storås, F. Fineide, H. L. Hammer, A. Khan, M. Magnø, C. Xiangjung, P. Halvorsen, T. Utheim and M. Riegler

Using explainable artificial intelligence (XAI) to explore factors affecting meibomian gland (MG) dropout

In ARVO Annual Meeting, 2023.
Status: Published
2022

Journal articles

M. Boeker, M. Riegler, H. L. Hammer, P. Jakobsen and P. Halvorsen

Prediction of Schizophrenia from Activity Data using Hidden Markov Model Parameters

Neural Computing and Applications (2022).
Status: Published
S. S. Eide, M. Riegler, H. L. Hammer and J. B. Bremnes

Deep Tower Networks for Efficient Temperature Forecasting from Multiple Data Sources

Sensors 22, no. 7 (2022): 2802.
Status: Published
H. L. Hammer, A. Yazidi and H. Rue

Estimating tukey depth using incremental quantile estimators

Pattern Recognition 122 (2022): 108339.
Status: Published
H. L. Hammer, A. Yazidi, M. Riegler and H. Rue

Efficient quantile tracking using an oracle

Applied Intelligence 53 (2022): 289-300.
Status: Published
S. Hicks, V. Thambawita, A. Storås, T. B. Haugen, H. L. Hammer, P. Halvorsen, M. Riegler and M. H. Stensen

Automatic Tracking of the ICSI procedure using Deep Learning

Human Reproduction 37, no. Supplement_1 (2022).
Status: Published
A. Sharma, R. Kakulavarapu, V. Thambawita, M. Siddiqui, E. Delbarre, M. Riegler, H. L. Hammer and M. Stensen

Automating tracking of cell division for human embryo development in time lapse videos

Human Reproduction 37, no. Supplement_1 (2022).
Status: Published