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Most recent publications

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
2020

Journal articles

H. Borgli, V. Thambawita, P. H. Smedsrud, S. Hicks, D. Jha, S. L. Eskeland, K. R. Randel, K. Pogorelov, M. Lux, D. T. D. Nguyen et al.

HyperKvasir, a comprehensive multi-class image and video dataset for gastrointestinal endoscopy

Scientific Data 7, no. 1 (2020): 1-14.
Status: Published
M. Kongshavn, H. Haugerud, A. Yazidi, T. Maseng, iv and H. L. Hammer

Mitigating DDoS using weight-based geographical clustering

Concurrency and Computation: Practice and Experience 32 (2020): e5679.
Status: Published
A. A. Mofrad, A. Yazidi, H. L. Hammer and E. Arntzen

Equivalence Projective Simulation as a Framework for Modeling Formation of Stimulus Equivalence Classes

Neural Computation 32 (2020): 912-968.
Status: Published
M. A. Pinto-Orellana and H. L. Hammer

Dyadic Aggregated Autoregressive Model (DASAR) for Automatic Modulation Classification

IEEE Access 8 (2020): 156096-156103.
Status: Published
S. Pontes-Filho, P. Lind, A. Yazidi, J. Zhang, H. L. Hammer, G. B. M. Mello, I. Sandvig, G. Tufte and S. Nichele

A neuro-inspired general framework for the evolution of stochastic dynamical systems: Cellular automata, random Boolean networks and echo state networks towards criticality

Cognitive Neurodynamics 14 (2020): 1-18.
Status: Published
V. Thambawita, D. Jha, H. L. Hammer, H. D. Johansen, D. Johansen, P. Halvorsen and M. Riegler

An Extensive Study on Cross-Dataset Bias and Evaluation Metrics Interpretation for Machine Learning applied to Gastrointestinal Tract Abnormality Classification

ACM Transactions on Computing for Healthcare 1 (2020): 1-29.
Status: Published