11 citations · 49 across the 25 of their papers we have counts for
25 papers
The Climber's Grip -- Personalized Deep Learning Models for Fear and Muscle Activity in Climbing
Matthias Boeker, Dana Swarbrick, Ulysse T. A. Côté-Allard +3
Climbing is a multifaceted sport that combines physical demands and emotional and cognitive challenges. Ascent styles differ in fall distance with lead climbing involving larger fa…
Calliope: A TTS-based Narrated E-book Creator Ensuring Exact Synchronization, Privacy, and Layout Fidelity
Hugo L. Hammer, Vajira Thambawita, Pål Halvorsen
A narrated e-book combines synchronized audio with digital text, highlighting the currently spoken word or sentence during playback. This format supports early literacy and assists…
ECG-IMN: Interpretable Mesomorphic Neural Networks for 12-Lead Electrocardiogram Interpretation
Vajira Thambawita, Jonas L. Isaksen, Jørgen K. Kanters +2
Deep learning has achieved expert-level performance in automated electrocardiogram (ECG) diagnosis, yet the "black-box" nature of these models hinders their clinical deployment. Tr…
VideoHEDGE: Entropy-Based Hallucination Detection for Video-VLMs via Semantic Clustering and Spatiotemporal Perturbations
Sushant Gautam, Cise Midoglu, Vajira Thambawita +2
Hallucinations in video-capable vision-language models (Video-VLMs) remain frequent and high-confidence, while existing uncertainty metrics often fail to align with correctness. We…
HEDGE: Hallucination Estimation via Dense Geometric Entropy for VQA with Vision-Language Models
Sushant Gautam, Michael A. Riegler, Pål Halvorsen
Vision-language models (VLMs) enable open-ended visual question answering but remain prone to hallucinations. We present HEDGE, a unified framework for hallucination detection that…
Evaluating LLMs on Generating Age-Appropriate Child-Like Conversations
Syed Zohaib Hassan, Pål Halvorsen, Miriam S. Johnson +1
Large Language Models (LLMs), predominantly trained on adult conversational data, face significant challenges when generating authentic, child-like dialogue for specialized applica…
Defending against Stegomalware in Deep Neural Networks with Permutation Symmetry
Birk Torpmann-Hagen, Michael A. Riegler, Pål Halvorsen +1
Deep neural networks are being utilized in a growing number of applications, both in production systems and for personal use. Network checkpoints are as a consequence often shared…
Medico 2025: Visual Question Answering for Gastrointestinal Imaging
Sushant Gautam, Vajira Thambawita, Michael Riegler +2
The Medico 2025 challenge addresses Visual Question Answering (VQA) for Gastrointestinal (GI) imaging, organized as part of the MediaEval task series. The challenge focuses on deve…
Multimodal Integration Challenges in Emotionally Expressive Child Avatars for Training Applications
Pegah Salehi, Sajad Amouei Sheshkal, Vajira Thambawita +2
Dynamic facial emotion is essential for believable AI-generated avatars, yet most systems remain visually static, limiting their use in simulations like virtual training for invest…
Kvasir-VQA-x1: A Multimodal Dataset for Medical Reasoning and Robust MedVQA in Gastrointestinal Endoscopy
Sushant Gautam, Michael A. Riegler, Pål Halvorsen
Medical Visual Question Answering (MedVQA) is a promising field for developing clinical decision support systems, yet progress is often limited by the available datasets, which can…
Point, Detect, Count: Multi-Task Medical Image Understanding with Instruction-Tuned Vision-Language Models
Sushant Gautam, Michael A. Riegler, Pål Halvorsen
We investigate fine-tuning Vision-Language Models (VLMs) for multi-task medical image understanding, focusing on detection, localization, and counting of findings in medical images…
SoccerChat: Integrating Multimodal Data for Enhanced Soccer Game Understanding
Sushant Gautam, Cise Midoglu, Vajira Thambawita +3
The integration of artificial intelligence in sports analytics has transformed soccer video understanding, enabling real-time, automated insights into complex game dynamics. Tradit…
Principal Components for Neural Network Initialization
Nhan Phan, Thu Nguyen, Uyen Dang +2
Principal Component Analysis (PCA) is a commonly used tool for dimension reduction and denoising. Therefore, it is also widely used on the data prior to training a neural network.…
Missing data imputation for noisy time-series data and applications in healthcare
Lien P. Le, Xuan-Hien Nguyen Thi, Thu Nguyen +3
Healthcare time series data is vital for monitoring patient activity but often contains noise and missing values due to various reasons such as sensor errors or data interruptions.…
Enhancing Naturalness in LLM-Generated Utterances through Disfluency Insertion
Syed Zohaib Hassan, Pierre Lison, Pål Halvorsen
Disfluencies are a natural feature of spontaneous human speech but are typically absent from the outputs of Large Language Models (LLMs). This absence can diminish the perceived na…
Comparative Analysis of Audio Feature Extraction for Real-Time Talking Portrait Synthesis
Pegah Salehi, Sajad Amouei Sheshkal, Vajira Thambawita +5
This paper examines the integration of real-time talking-head generation for interviewer training, focusing on overcoming challenges in Audio Feature Extraction (AFE), which often…
SoccerGuard: Investigating Injury Risk Factors for Professional Soccer Players with Machine Learning
Finn Bartels, Lu Xing, Cise Midoglu +3
We present SoccerGuard, a novel framework for predicting injuries in women's soccer using Machine Learning (ML). This framework can ingest data from multiple sources, including sub…
Enhancing Structured-Data Retrieval with GraphRAG: Soccer Data Case Study
Zahra Sepasdar, Sushant Gautam, Cise Midoglu +2
Extracting meaningful insights from large and complex datasets poses significant challenges, particularly in ensuring the accuracy and relevance of retrieved information. Tradition…
PolypDB: A Curated Multi-Center Dataset for Development of AI Algorithms in Colonoscopy
Debesh Jha, Nikhil Kumar Tomar, Vanshali Sharma +19
Colonoscopy is the primary method for examination, detection, and removal of polyps. However, challenges such as variations among the endoscopists' skills, bowel quality preparatio…
PLayerTV: Advanced Player Tracking and Identification for Automatic Soccer Highlight Clips
Håkon Maric Solberg, Mehdi Houshmand Sarkhoosh, Sushant Gautam +3
In the rapidly evolving field of sports analytics, the automation of targeted video processing is a pivotal advancement. We propose PlayerTV, an innovative framework which harnesse…
Demo: Soccer Information Retrieval via Natural Queries using SoccerRAG
Aleksander Theo Strand, Sushant Gautam, Cise Midoglu +1
The rapid evolution of digital sports media necessitates sophisticated information retrieval systems that can efficiently parse extensive multimodal datasets. This paper demonstrat…
SoccerRAG: Multimodal Soccer Information Retrieval via Natural Queries
Aleksander Theo Strand, Sushant Gautam, Cise Midoglu +1
The rapid evolution of digital sports media necessitates sophisticated information retrieval systems that can efficiently parse extensive multimodal datasets. This paper introduces…
Soccer on Social Media
Mehdi Houshmand Sarkhoosh, Sayed Mohammad Majidi Dorcheh, Sushant Gautam +3
In the era of digitalization, social media has become an integral part of our lives, serving as a significant hub for individuals and businesses to share information, communicate,…
Grand Challenge On Detecting Cheapfakes
Duc-Tien Dang-Nguyen, Sohail Ahmed Khan, Cise Midoglu +3
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 media…