Hugo Hammer

N. Papachrysos, P. H. Smedsrud, K. V. Ånonsen, T. J. D. Berstad, H. Espeland, A. Petlund, P. Hedenström, P. Halvorsen, J. Varkey, H. L. Hammer, M. Riegler and T. de Lange

A comparative study benchmarking colon polyp with computer-aided detection (CADe) software

DEN Open

A. Storås, S. Mæland, J. Isaksen, S. Hicks, V. Thambawita, C. Graff, H. L. Hammer, P. Halvorsen, M. Riegler and J. Kanters

Evaluating gradient-based explanation methods for neural network ECG analysis using heatmaps

JAMIA

T. L. Vo, T. Nguyen, L. M. Lopez-Ramos, H. L. Hammer, M. Riegler and P. Halvorsen

Explainability of Machine Learning Models under Missing Data

Applied Soft Computing

H. L. Hammer and S. A. Sheshkal

Classifying Dry Eye Disease Patients from Healthy Controls Using Machine Learning and Metabolomics Data

Diagnostics

N. Papachrysos, P. H. Smedsrud, K. V. Ånonsen, T. J. D. Berstad, H. Espeland, A. Petlund, P. Hedenström, P. Halvorsen, J. Varkey, H. L. Hammer, M. Riegler and T. de Lange

A comparative study benchmarking colon polyp detection with CADe software

Endoscopy

H. Svennevik, S. Hicks, M. Riegler, T. Storelvmo and H. L. Hammer

A dataset for predicting cloud cover over Europe

Scientific Data

M. Vo, T. Nguyen, M. Riegler and H. L. Hammer

Efficient Estimation of Generative Models Using Tukey Depth

Algorithms

M. Boeker, D. Swarbrick, U. Côté-Allard, M. Riegler, P. Halvorsen and H. L. Hammer

Predictive Modelling of Muscle Fatigue in Climbing

MMSports '24: Proceedings of the 7th ACM International Workshop on Multimedia Content Analysis in Sports

A. Sharma, F. Alawad, R. Kakulavarapu, M. Iliceto, M. Riegler, M. Stensen and H. L. Hammer

Exploring Embryo Development at the Morula Stage-an AI-based Approach to Determine Whether to Use or Discard an Embryo

2024 4th International Conference on Applied Artificial Intelligence (ICAPAI)

A. Sharma, A. Z. Ansari, K. Radhika, M. Stensen, M. Riegler and H. L. Hammer

Predicting Cell Cleavage Timings from Time-Lapse Videos of Human Embryos

Big Data and Cognitive Computing

M. Q. Vo, T. Nguyen, M. Riegler and H. L. Hammer

Efficient Estimation of Generative Models using Tukey Depth

NA

M. Boeker, P. Jakobsen, M. Riegler, L. Stabell, O. B. Fasmer, P. Halvorsen and H. L. Hammer

Affect Recognition in Muscular Response Signals

IEEE Access

H. H. Thunold and H. L. Hammer

A Deep Diagnostic Framework Using Explainable Artificial Intelligence and Clustering

Diagnostics

V. Thambawita, S. Hicks, A. Storås, T. Nguyen, J. M. Andersen, O. Witczak, T. B. Haugen, H. L. Hammer, P. Halvorsen and M. Riegler

VISEM-Tracking, a human spermatozoa tracking dataset

Scientific Data

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

Approximate Bayesian Inference Based on Expected Evaluation

Bayesian Analysis

T. Nguyen, H. T. Ly, M. Riegler, P. Halvorsen and H. L. Hammer

Principal Components Analysis based frameworks for efficient missing data imputation algorithms

Recent Challenges in Intelligent Information and Database Systems. ACIIDS 2023

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

Investigative Ophthalmology & Visual Science, ARVO Annual Meeting

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

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

Investigative Ophthalmology & Visual Science, ARVO Annual Meeting

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

Nordic Artificial Intelligence Research and Development

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

V. Thambawita, S. Hicks, A. Storås, O. Witczak, J. M. Andersen, H. L. Hammer, P. Halvorsen, M. Riegler and H. B. Trine

Real-time deep learning based multi object tracking of spermatozoa in fresh samples

Human Reproduction

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

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

H. L. Hammer, A. Yazidi, M. Riegler and H. Rue

Efficient quantile tracking using an oracle

Applied Intelligence

V. Thambawita, P. Salehi, S. A. Sheshkal, S. Hicks, H. L. Hammer, S. Parasa, T. de Lange, P. Halvorsen and M. Riegler

SinGAN-Seg: Synthetic training data generation for medical image segmentation

PLOS ONE

A. Storås, R. Prabhu, H. L. Hammer and I. Strümke

Bias og kvantitativ analyse innen velferd

Tidsskrift for velferdsforskning

S. S. Eide, M. Riegler, H. L. Hammer and J. B. Bremnes

Deep Tower Networks for Efficient Temperature Forecasting from Multiple Data Sources

Sensors

H. L. Hammer, A. Yazidi and H. Rue

Estimating tukey depth using incremental quantile estimators

Pattern Recognition

A. Storås, I. Strümke, M. Riegler, J. Grauslund, H. L. Hammer, A. Yazidi, P. Halvorsen, K. G. Gundersen, T. P. Utheim and C. J. Jackson

Artificial intelligence in dry eye disease

The Ocular Surface

V. Thambawita, S. Hicks, A. Storås, J. M. Andersen, O. Witczak, T. B. Haugen, H. L. Hammer, T. Nguyen, P. Halvorsen and M. Riegler

Medico Multimedia Task at MediaEval 2022: Transparent Tracking of Spermatozoa

MediaEval 2022

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

A. Sharma, M. H. Stensen, E. Delbarre, T. B. Haugen and H. L. Hammer

Explainable Artificial Intelligence for Human Embryo Cell Cleavage Stages Analysis

Proceedings of the 3rd ACM Workshop on Intelligent Cross-Data Analysis and Retrieval

A. Storås, M. Riegler, T. B. Haugen, V. Thambawita, S. Hicks, H. L. Hammer, R. Kakulavarapu, P. Halvorsen and M. Stensen

Automatic Unsupervised Clustering of Videos of the Intracytoplasmic Sperm Injection (ICSI) Procedure

NAIS: Symposium of the Norwegian AI Society

A. Sharma, T. Haugen, H. L. Hammer, M. Riegler and M. Stensen

Towards better explainable deep learning models for embryo selection in ART

Human Reproduction

M. Riegler, M. H. Stensen, O. Witczak, J. M. Andersen, S. Hicks, H. L. Hammer, E. Delbarre, P. Halvorsen, A. Yazidi, N. Holst and T. B. Haugen

Artificial intelligence in the fertility clinic: status, pitfalls and possibilities

Human Reproduction

V. Thambawita, J. L. Isaksen, S. Hicks, J. Ghouse, G. Ahlberg, A. Linneberg, N. Grarup, C. Ellervik, M. S. Olesen, T. Hansen, C. Graff, N. Holstein-Rathlou, I. Strümke, H. L. Hammer, M. Maleckar, P. Halvorsen, M. Riegler and J. K. Kanters

DeepFake electrocardiograms using generative adversarial networks are the beginning of the end for privacy issues in medicine

Nature Scientific Reports

H. Svennevik, M. Riegler, S. Hicks, T. Storelvmo and H. L. Hammer

Prediction of Cloud Fractional Cover Using Machine Learning

Big Data and Cognitive Computing

V. Thambawita, J. L. Isaksen, S. Hicks, J. Ghouse, G. Ahlberg, A. Linneberg, N. Grarup, C. Ellervik, M. S. Olesen, T. Hansen, C. Graff, N. Holstein-Rathlou, I. Strümke, H. L. Hammer, M. Maleckar, P. Halvorsen, M. Riegler and J. K. Kanters

DeepFake electrocardiograms: the key for open science for artificial intelligence in medicine

Scientific Reports

A. Kolevatova, M. Riegler, F. Cherubini, X. Hu and H. L. Hammer

Unraveling the Impact of Land Cover Changes on Climate using Machine Learning and Explainable Artificial Intelligence

Big Data and Cognitive Computing

H. L. Hammer, A. Yazidi and H. Rue

Joint tracking of multiple quantiles through conditional quantiles

Information Sciences

P. H. Smedsrud, V. Thambawita, S. Hicks, H. Gjestang, O. O. Nedrejord, E. Næss, H. Borgli, D. Jha, T. J. D. Berstad, S. L. Eskeland, M. Lux, H. Espeland, A. Petlund, D. T. D. Nguyen, E. Garcia-Ceja, D. Johansen, P. T. Schmidt, E. Toth, H. L. Hammer, T. de Lange, M. Riegler and P. Halvorsen

Kvasir-Capsule, a video capsule endoscopy dataset

Scientific Data

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

Diagnosing Schizophrenia from Activity Records using Hidden Markov Model Parameters

2021 IEEE 34th International Symposium on Computer-Based Medical Systems (CBMS)2021 IEEE 34th International Symposium on Computer-Based Medical Systems (CBMS)

S. Hicks, D. Jha, V. Thambawita, H. L. Hammer, T. de Lange, S. Parasa, M. Riegler and P. Halvorsen

Medico Multimedia Task at MediaEval 2021: Transparency in Medical Image Segmentation

Mediaeval Medico 2021

S. S. Eide, M. Riegler, H. L. Hammer and J. B. Bremnes

Temperature Forecasting using Tower Networks

Proceedings of the 2021 Workshop on Intelligent Cross-Data Analysis and Retrieval

S. Hicks, A. Stautland, O. B. Fasmer, W. Frøland, H. L. Hammer, P. Halvorsen, K. Mjeldheim, K. J. Oedegaard, B. Osnes, V. E. G. Syrstad, M. Riegler and P. Jakobsen

HYPERAKTIV: An Activity Dataset from Patients with Attention-Deficit/Hyperactivity Disorder (ADHD)

Proceedings of the 12th ACM Multimedia Systems Conference (MMSys '21)

V. Thambawita, T. B. Haugen, M. Stensen, O. Witczak, H. L. Hammer, P. Halvorsen and M. Riegler

Identification of spermatozoa by unsupervised learning from video data

37th Virtual Annual Meeting of the European Society of Human Reproduction and Embryology (ESHRE)

V. Thambawita, S. Hicks, J. Isaksen, M. H. Stensen, T. B. Haugen, J. Kanters, S. Parasa, T. de Lange, H. D. Johansen, D. Johansen, H. L. Hammer, P. Halvorsen and M. Riegler

DeepSynthBody: the beginning of the end for data deficiency in medicine

The International Conference on Applied Artificial Intelligence (ICAPAI)

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

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

M. A. Pinto-Orellana and H. L. Hammer

Analysis of Optical Brain Signals Using Connectivity Graph Networks

International Cross-Domain Conference for Machine Learning and Knowledge Extraction