Search Results for author: Michael Riegler

Found 13 papers, 5 papers with code

Advancing sleep detection by modelling weak label sets: A novel weakly supervised learning approach

no code implementations27 Feb 2024 Matthias Boeker, Vajira Thambawita, Michael Riegler, Pål Halvorsen, Hugo L. Hammer

A \gls{lstm} trained on the soft cross-entropy outperformed conventional sleep detection algorithms, other neural network architectures and loss functions in accuracy and model calibration.

Weakly-supervised Learning

Grand Challenge On Detecting Cheapfakes

1 code implementation3 Apr 2023 Duc-Tien Dang-Nguyen, Sohail Ahmed Khan, Cise Midoglu, Michael Riegler, Pål Halvorsen, Minh-Son Dao

OOC media is much harder to detect than fake media, since the images and videos are not tampered.

Image Captioning

Visual explanations for polyp detection: How medical doctors assess intrinsic versus extrinsic explanations

1 code implementation23 Mar 2022 Steven Hicks, Andrea Storås, Michael Riegler, Cise Midoglu, Malek Hammou, Thomas de Lange, Sravanthi Parasa, Pål Halvorsen, Inga Strümke

Deep learning has in recent years achieved immense success in all areas of computer vision and has the potential of assisting medical doctors in analyzing visual content for disease and other abnormalities.

Explainable artificial intelligence

Parallel feature selection based on the trace ratio criterion

no code implementations3 Mar 2022 Thu Nguyen, Thanh Nhan Phan, Van Nhuong Nguyen, Thanh Binh Nguyen, Pål Halvorsen, Michael Riegler

The experiments show that our method can produce a small set of features in a fraction of the amount of time by the other methods under comparison.

feature selection Management

MedAI: Transparency in Medical Image Segmentation

1 code implementation Nordic Machine Intelligence 2021 Steven Hicks, Debesh Jha, Vajira Thambawita, Pål Halvorsen, Bjørn-Jostein Singstad, Sachin Gaur, Klas Pettersen, Morten Goodwin, Sravanthi Parasa, Thomas de Lange, Michael Riegler

MedAI: Transparency in Medical Image Segmentation is a challenge held for the first time at the Nordic AI Meet that focuses on medical image segmentation and transparency in machine learning (ML)-based systems.

Image Segmentation Medical Image Segmentation +2

Common Limitations of Image Processing Metrics: A Picture Story

1 code implementation12 Apr 2021 Annika Reinke, Minu D. Tizabi, Carole H. Sudre, Matthias Eisenmann, Tim Rädsch, Michael Baumgartner, Laura Acion, Michela Antonelli, Tal Arbel, Spyridon Bakas, Peter Bankhead, Arriel Benis, Matthew Blaschko, Florian Buettner, M. Jorge Cardoso, Jianxu Chen, Veronika Cheplygina, Evangelia Christodoulou, Beth Cimini, Gary S. Collins, Sandy Engelhardt, Keyvan Farahani, Luciana Ferrer, Adrian Galdran, Bram van Ginneken, Ben Glocker, Patrick Godau, Robert Haase, Fred Hamprecht, Daniel A. Hashimoto, Doreen Heckmann-Nötzel, Peter Hirsch, Michael M. Hoffman, Merel Huisman, Fabian Isensee, Pierre Jannin, Charles E. Kahn, Dagmar Kainmueller, Bernhard Kainz, Alexandros Karargyris, Alan Karthikesalingam, A. Emre Kavur, Hannes Kenngott, Jens Kleesiek, Andreas Kleppe, Sven Kohler, Florian Kofler, Annette Kopp-Schneider, Thijs Kooi, Michal Kozubek, Anna Kreshuk, Tahsin Kurc, Bennett A. Landman, Geert Litjens, Amin Madani, Klaus Maier-Hein, Anne L. Martel, Peter Mattson, Erik Meijering, Bjoern Menze, David Moher, Karel G. M. Moons, Henning Müller, Brennan Nichyporuk, Felix Nickel, M. Alican Noyan, Jens Petersen, Gorkem Polat, Susanne M. Rafelski, Nasir Rajpoot, Mauricio Reyes, Nicola Rieke, Michael Riegler, Hassan Rivaz, Julio Saez-Rodriguez, Clara I. Sánchez, Julien Schroeter, Anindo Saha, M. Alper Selver, Lalith Sharan, Shravya Shetty, Maarten van Smeden, Bram Stieltjes, Ronald M. Summers, Abdel A. Taha, Aleksei Tiulpin, Sotirios A. Tsaftaris, Ben van Calster, Gaël Varoquaux, Manuel Wiesenfarth, Ziv R. Yaniv, Paul Jäger, Lena Maier-Hein

While the importance of automatic image analysis is continuously increasing, recent meta-research revealed major flaws with respect to algorithm validation.

Instance Segmentation object-detection +2

Visual Sentiment Analysis from Disaster Images in Social Media

no code implementations4 Sep 2020 Syed Zohaib Hassan, Kashif Ahmad, Steven Hicks, Paal Halvorsen, Ala Al-Fuqaha, Nicola Conci, Michael Riegler

While sentiment analysis of text streams has been widely explored in literature, sentiment analysis from images and videos is relatively new.

Humanitarian Model Selection +1

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

no code implementations8 Nov 2019 Vajira Thambawita, Pål Halvorsen, Hugo Hammer, Michael Riegler, Trine B. Haugen

To solve this regression task of predicting motility and morphology, stacked dense optical flows and extracted original frames from sperm videos were used with the modified state of the art convolution neural networks.


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

1 code implementation8 Nov 2019 Vajira Thambawita, Pål Halvorsen, Hugo Hammer, Michael Riegler, Trine B. Haugen

In this paper, we present a two-step deep learning method that is used to predict sperm motility and morphology-based on video recordings of human spermatozoa.

Transfer Learning

Multi-Modal Machine Learning for Flood Detection in News, Social Media and Satellite Sequences

no code implementations7 Oct 2019 Kashif Ahmad, Konstantin Pogorelov, Mohib Ullah, Michael Riegler, Nicola Conci, Johannes Langguth, Ala Al-Fuqaha

In this paper we present our methods for the MediaEval 2019 Mul-timedia Satellite Task, which is aiming to extract complementaryinformation associated with adverse events from Social Media andsatellites.

BIG-bench Machine Learning

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