469 citations · 1.5k across the 48 of their papers we have counts for
15 papers · 1 filter
VISEM-Tracking, a human spermatozoa tracking dataset
Vajira Thambawita, Steven A. Hicks, Andrea M. Storås +7
A manual assessment of sperm motility requires microscopy observation, which is challenging due to the fast-moving spermatozoa in the field of view. To obtain correct results, manu…
MLC at HECKTOR 2022: The Effect and Importance of Training Data when Analyzing Cases of Head and Neck Tumors using Machine Learning
Vajira Thambawita, Andrea M. Storås, Steven A. Hicks +2
Head and neck cancers are the fifth most common cancer worldwide, and recently, analysis of Positron Emission Tomography (PET) and Computed Tomography (CT) images has been proposed…
Combining datasets to increase the number of samples and improve model fitting
Thu Nguyen, Rabindra Khadka, Nhan Phan +3
For many use cases, combining information from different datasets can be of interest to improve a machine learning model's performance, especially when the number of samples from a…
ACM Multimedia Grand Challenge on Detecting Cheapfakes
Shivangi Aneja, Cise Midoglu, Duc-Tien Dang-Nguyen +5
Cheapfake is a recently coined term that encompasses non-AI (``cheap'') manipulations of multimedia content. Cheapfakes are known to be more prevalent than deepfakes. Cheapfake med…
Towards the Neuroevolution of Low-level Artificial General Intelligence
Sidney Pontes-Filho, Kristoffer Olsen, Anis Yazidi +3
In this work, we argue that the search for Artificial General Intelligence (AGI) should start from a much lower level than human-level intelligence. The circumstances of intelligen…
Video Analytics in Elite Soccer: A Distributed Computing Perspective
Debesh Jha, Ashish Rauniyar, Håvard D. Johansen +4
Ubiquitous sensors and Internet of Things (IoT) technologies have revolutionized the sports industry, providing new methodologies for planning, effective coordination of training,…
Metrics reloaded: Recommendations for image analysis validation
Lena Maier-Hein, Annika Reinke, Patrick Godau +71
Increasing evidence shows that flaws in machine learning (ML) algorithm validation are an underestimated global problem. Particularly in automatic biomedical image analysis, chosen…
Segmentation Consistency Training: Out-of-Distribution Generalization for Medical Image Segmentation
Birk Torpmann-Hagen, Vajira Thambawita, Kyrre Glette +2
Generalizability is seen as one of the major challenges in deep learning, in particular in the domain of medical imaging, where a change of hospital or in imaging routines can lead…
PolypConnect: Image inpainting for generating realistic gastrointestinal tract images with polyps
Jan Andre Fagereng, Vajira Thambawita, Andrea M. Storås +4
Early identification of a polyp in the lower gastrointestinal (GI) tract can lead to prevention of life-threatening colorectal cancer. Developing computer-aided diagnosis (CAD) sys…
Grid HTM: Hierarchical Temporal Memory for Anomaly Detection in Videos
Vladimir Monakhov, Vajira Thambawita, Pål Halvorsen +1
The interest for video anomaly detection systems has gained traction for the past few years. The current approaches use deep learning to perform anomaly detection in videos, but th…
Predicting tacrolimus exposure in kidney transplanted patients using machine learning
Andrea M. Storås, Anders Åsberg, Pål Halvorsen +2
Tacrolimus is one of the cornerstone immunosuppressive drugs in most transplantation centers worldwide following solid organ transplantation. Therapeutic drug monitoring of tacroli…
Principal Component Analysis based frameworks for efficient missing data imputation algorithms
Thu Nguyen, Hoang Thien Ly, Michael Alexander Riegler +2
Missing data is a commonly occurring problem in practice. Many imputation methods have been developed to fill in the missing entries. However, not all of them can scale to high-dim…
Visual explanations for polyp detection: How medical doctors assess intrinsic versus extrinsic explanations
Steven Hicks, Andrea Storås, Michael Riegler +6
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 diseas…
Parallel feature selection based on the trace ratio criterion
Thu Nguyen, Thanh Nhan Phan, Van Nhuong Nguyen +3
The growth of data today poses a challenge in management and inference. While feature extraction methods are capable of reducing the size of the data for inference, they do not hel…
Assessing generalisability of deep learning-based polyp detection and segmentation methods through a computer vision challenge
Sharib Ali, Noha Ghatwary, Debesh Jha +29
Polyps are well-known cancer precursors identified by colonoscopy. However, variability in their size, location, and surface largely affect identification, localisation, and charac…