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2021
T. B. Haugen, S. Hicks, O. Witczak, J. M. Andersen, L. Bjørndal, M. Riegler and M. H. Stensen. Assessment of sperm motility according to WHO classification using convolutional neural networks. ESHRE: ESHRE, 2021.
T. B. Haugen, S. Hicks, O. Witczak, J. M. Andersen, L. Bjørndal, M. Riegler and M. H. Stensen. Assessment of sperm motility according to WHO classification using convolutional neural networks. ESHRE: ESHRE, 2021.
D. Jha, S. Ali, S. Hicks, V. Thambawita, H. Borgli, P. H. Smedsrud, T. de Lange, K. Pogorelov, X. Wang, P. Harzig et al. "A comprehensive analysis of classification methods in gastrointestinal endoscopy imaging." Medical Image Analysis (2021).PDF icon 2.pdf (3.22 MB)
D. Jha, P. H. Smedsrud, D. Johansen, T. de Lange, H. D. Johansen, P. Halvorsen and M. Riegler. "A Comprehensive Study on Colorectal Polyp Segmentation with ResUNet++, Conditional Random Field and Test-Time Augmentation." IEEE Journal of Biomedical and Health Informatics (2021).PDF icon 09314114.pdf (6.16 MB)
N. K. Tomar, D. Jha, S. Ali, H. D. Johansen, D. Johansen, M. Riegler and P. Halvorsen. DDANet: Dual Decoder Attention Network for Automatic Polyp Segmentation In 25th International Conference on Pattern Recognition . Springer, 2021.PDF icon endotect_segmentation_debesh.pdf (4.12 MB)
V. Thambawita, S. Hicks, J. Isaksen, M. H. Stensen, T. B. Haugen, J. Kanters, S. Parasa, T. de Lange, H. D. Johansen, D. Johansen et al. DeepSynthBody: the beginning of the end for data deficiency in medicine In The International Conference on Applied Artificial Intelligence (ICAPAI)., 2021.
V. Thambawita, S. Hicks, P. Halvorsen and M. Riegler. DivergentNets: Medical Image Segmentation by Network Ensemble In EndoCV., 2021.
S. Hicks, J. L. Isaksen, V. Thambawita, J. Ghouse, G. Ahlberg, A. Linneberg, N. Grarup, I. Strümke, C. Ellervik, M. S. Olesen et al. "Explaining deep neural networks for knowledge discovery in electrocardiogram analysisAbstract." Scientific Reports 11 (2021).
V. Thambawita, I. Strümke, S. Hicks, M. Riegler, P. Halvorsen and S. Parasa. Generative Adversarial Networks For Creating Realistic Artificial Colon Polyp Images In DDW., 2021.
E. Garcia-Ceja, V. Thambawita, S. Hicks, D. Jha, P. Jakobsen, H. L. Hammer, P. Halvorsen and M. Riegler. HTAD: A Home-Tasks Activities Dataset with Wrist-accelerometer and Audio Features In 27th International Conference on Multimedia Modeling. Springer, 2021.PDF icon mmm_2021_dataset_htad.pdf (637.46 KB)
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 In ESHRE ., 2021.
V. Thambawita, S. Hicks, I. Strümke, M. Riegler, P. Halvorsen and S. Parasa. Impact of Image Resolution on Convolutional Neural Networks Performance in Gastrointestinal Endoscopy In DDW., 2021.
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 et al. "Kvasir-Capsule, a video capsule endoscopy dataset ." Scientific Data 8, no. 1 (2021).
D. Jha, S. Ali, K. Emanuelsen, S. Hicks, V. Thambawita, E. Garcia-Ceja, M. Riegler, T. de Lange, P. T. Schmidt, H. D. Johansen et al. Kvasir-Instrument: Diagnostic and therapeutic tool segmentation dataset in gastrointestinal endoscopy In 27th International Conference on Multimedia Modeling. MMM 2021, 2021.PDF icon mmm.pdf (648.64 KB)
D. Jha, N. K. Tomar, S. Ali, M. Riegler, H. D. Johansen, D. Johansen, T. de Lange and P. Halvorsen. NanoNet: Real-Time Polyp Segmentation in Video Capsule Endoscopy and Colonoscopy In 34th IEEE CBMS International Symposium on Computer-Based Medical Systems. IEEE, 2021.PDF icon 412100a037.pdf (789.29 KB)
D. Jha, S. Ali, N. K. Tomar, H. D. Johansen, D. Johansen, J. Rittscher, M. Riegler and P. Halvorsen. "Real-Time Polyp Detection, Localization and Segmentation in Colonoscopy Using Deep Learning." IEEE Access (2021).PDF icon 09369308.pdf (2.6 MB)
2020
S. Hicks, V. Thambawita, H. L. Hammer, T. B. Haugen, J. M. Andersen, O. Witczak, P. Halvorsen and M. Riegler. ACM Multimedia BioMedia 2020 Grand Challenge Overview In Proceedings of the 28th ACM International Conference on Multimedia. New York, NY, USA: Association for Computing Machinery, 2020.
P. Jakobsen, E. Garcia-Ceja, M. Riegler, L. A. Stabell, T. Nordgreen, J. Torresen, O. B. Fasmer and K. J. Oedegaard. "Applying machine learning in motor activity time series of depressed bipolar and unipolar patients compared to healthy controls." PLOS ONE 15, no. 8 (2020): e0231995.
S. Hicks, T. B. Haugen, M. Iliceto, H. L. Hammer, J. M. Andersen, O. Witczak, M. Riegler and M. Stensen. Big data is not always better – prediction of live birth using machine learning on time-lapse videos of human embryos. ESHRE virtual 36th Annual Meeting: ESHRE, 2020.
T. Roß, A. Reinke, P. M. Full, M. Wagner, H. Kenngott, M. Apitz, H. Hempe, D. M. Filimon, P. Scholz, T. N. Tran et al. "Comparative validation of multi-instance instrument segmentation in endoscopy: results of the ROBUST-MIS 2019 challenge." Medical Image Analysis (2020).PDF icon 1.pdf (6.18 MB)
D. Jha, M. Riegler, D. Johansen, P. Halvorsen and H. D. Johansen. DoubleU-Net: A Deep Convolutional Neural Network for Medical Image Segmentation In CBMS 2020: International Symposium on Computer-Based Medical Systems. IEEE, 2020.PDF icon 09183321_1.pdf (1.15 MB)
S. Hicks, D. Jha, V. Thambawita, P. Halvorsen, H. L. Hammer and M. Riegler. The EndoTect 2020 Challenge: Evaluation and Comparison of Classification, Segmentation and Inference Time for Endoscopy In 25th International Conference on Pattern Recognition (ICPR). IEEE, 2020.
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.PDF icon 3386295.pdf (8.11 MB)
E. Garcia-Ceja, B. Morin, A. Aguilar-Rivera and M. Riegler. "A Genetic Attack Against Machine Learning Classifiers to Steal Biometric Actigraphy Profiles from Health Related Sensor Data." Journal of Medical Systems 44, no. 10 (2020): 1-11.
F. M. Noori, M. Riegler, M. Z. Uddin and J. Torresen. "Human Activity Recognition from Multiple Sensors Data Using Multi-fusion Representations and CNNs." ACM Transactions on Multimedia Computing, Communications, and Applications 16, no. 2 (2020): 1-19.

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