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Michael Riegler
Chief Research Scientist/Research Professor
Organisation:
Holistic Systems
Email:
michael@simula.no
Research interests:
Multimedia & Medical Multimedia
User Intent
Serious Games
Crowdsourcing
Machine Learning
Selected publications
M. Riegler
,
M. Lux
and
C. Kofler
How 'How' Reflects What's What: Content-based Exploitation of How Users Frame Social Images
In
MM '14: Proceedings of the ACM International Conference on Multimedia
. New York, NY, USA: ACM, 2014.
Proceedings, refereed
2014
View
M. Riegler
,
L. Calvet
,
A. Calvet
,
P. Halvorsen
and
C. Griwodz
Exploitation of Producer Intent in Relation to Bandwidth and QoE for Online Video Streaming Services
In
NOSSDAV at Multimedia Systems Conference
. Portland, USA: ACM, 2015.
Proceedings, refereed
2015
View
M. Riegler
,
K. Pogorelov
,
S. L. Eskeland
,
P. T. Schmidt
,
Z. Albisser
,
D. Johansen
,
C. Griwodz
,
P. Halvorsen
and
T. de Lange
From Annotation to Computer-Aided Diagnosis: Detailed Evaluation of a Medical Multimedia System
ACM Transactions on Multimedia Computing, Communications, and Applications
13, no. 3 (2017).
Journal Article
2017
View
M. Riegler
,
C. Griwodz
,
C. Spampinato
,
T. de Lange
,
S. L. Eskeland
,
K. Pogorelov
,
W. Tavanapong
,
P. T. Schmidt
,
C. Gurrin
,
D. Johansen
et al.
Multimedia and Medicine: Teammates for Better Disease Detection and Survival
In
ACM Multimedia
. Amsterdam, The Netherlands, The Netherlands: ACM, 2016.
Proceedings, refereed
2016
View
News
21 December 2020
Two Simula projects funded by the Research Council of Norway
1 of 5
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Available Master's topics
Adaptive Tests for Memory Training using Asymmetric Search Point Location
Automatic detection of abnormal video events in sport videos
Automatic generation of sport highlights
Automatic video event clipping in sports
Big Data Visualization for Crowdsourced Network Measurements
Development and evaluation of new GAN models and estimation techniques
Development of diagnosis support system for endoscopic images using machine learning
Development of generalizable DL models for gastrointestinal disease segmentation
Explaining the Predictions of a Deep Neural Network used to Analyze Videos of Human Semen.
Exploring the Use of Synthetic Data for Deep Learning in Sparse Data Domains
Generative Adversarial Network Models for electoral behaviours studies
Machine Learning for Real-Time Applications
Machine Learning in PCIe networks
Polyps segmentation using synthetic images generated by conditionalGAN
Short-term precipitation forecasting with deep neural nets
Sport news classification
Time series analysis via Residual Neural Networks
Unsupervised way to segment sperm sample images using CycleGAN for predicting motility and morphology levels
Using Machine Learning to generate Virtual Avatars
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Year published
2021
(4)
2020
(27)
2019
(52)
2018
(34)
2017
(29)
2016
(23)
2015
(10)
2014
(11)
2013
(3)
2005