Trine Haugen

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

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

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

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

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

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

Extracting temporal features into a spatial domain using autoencoders for sperm video analysis

MediaEval 2019

S. Hicks, P. Halvorsen, T. B. Haugen, J. M. Andersen, O. Witczak, K. Pogorelov, H. L. Hammer, D. Dang-Nguyen, M. Lux and M. Riegler

Medico Multimedia Task at MediaEval 2019

MediaEval

S. Hicks, P. Halvorsen, T. B. Haugen, J. M. Andersen, O. Witczak, K. Pogorelov, H. L. Hammer, D. Dang-Nguyen, M. Lux and M. Riegler

Predicting Sperm Motility and Morphology using Deep Learning and Handcrafted Features

MediaEval

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

Stacked dense optical flows and dropout layers to predict sperm motility and morphology

MediaEval 2019, 27-29 October 2019, Sophia Antipolis, France

S. Hicks, T. B. Haugen, P. Halvorsen and M. Riegler

Using Deep Learning to Predict Motility and Morphology of Human Sperm

MediaEval 2019