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View article: FAIR Data Assessment Using LLMs: The Fair-Way
FAIR Data Assessment Using LLMs: The Fair-Way Open
As part of modern research practices, the FAIR data principles have become essential for data discoverability, usability, and sharing. Existing implementations for automatically assessing FAIR adherence (FAIRness) often suffer from limited…
View article: MoiréNet: A Compact Dual-Domain Network for Image Demoiréing
MoiréNet: A Compact Dual-Domain Network for Image Demoiréing Open
Moiré patterns arise from spectral aliasing between display pixel lattices and camera sensor grids, manifesting as anisotropic, multi-scale artifacts that pose significant challenges for digital image demoiréing. We propose MoiréNet, a con…
View article: Towards Systematic Specification and Verification of Fairness Requirements: A Position Paper
Towards Systematic Specification and Verification of Fairness Requirements: A Position Paper Open
Decisions suggested by improperly designed software systems might be prone to discriminate against people based on protected characteristics, such as gender and ethnicity. Previous studies attribute such undesired behavior to flaws in algo…
View article: Unleashing Semantic and Geometric Priors for 3D Scene Completion
Unleashing Semantic and Geometric Priors for 3D Scene Completion Open
Camera-based 3D semantic scene completion (SSC) provides dense geometric and semantic perception for autonomous driving and robotic navigation. However, existing methods rely on a coupled encoder to deliver both semantic and geometric prio…
View article: EMORL: Ensemble Multi-Objective Reinforcement Learning for Efficient and Flexible LLM Fine-Tuning
EMORL: Ensemble Multi-Objective Reinforcement Learning for Efficient and Flexible LLM Fine-Tuning Open
Recent advances in reinforcement learning (RL) for large language model (LLM) fine-tuning show promise in addressing multi-objective tasks but still face significant challenges, including competing objective balancing, low training efficie…
View article: FDO Manager: Minimum Viable FAIR Digital Object Implementation
FDO Manager: Minimum Viable FAIR Digital Object Implementation Open
In the digital age, data has emerged as one of the most valuable assets across various sectors, including academia, industry, and healthcare. Effective data preservation involves the management of data to ensure its long-term accessibility…
View article: ELMTEX: Fine-Tuning Large Language Models for Structured Clinical Information Extraction. A Case Study on Clinical Reports
ELMTEX: Fine-Tuning Large Language Models for Structured Clinical Information Extraction. A Case Study on Clinical Reports Open
Europe's healthcare systems require enhanced interoperability and digitalization, driving a demand for innovative solutions to process legacy clinical data. This paper presents the results of our project, which aims to leverage Large Langu…
View article: Comparison of Feature Learning Methods for Metadata Extraction from PDF Scholarly Documents
Comparison of Feature Learning Methods for Metadata Extraction from PDF Scholarly Documents Open
The availability of metadata for scientific documents is pivotal in propelling scientific knowledge forward and for adhering to the FAIR principles (i.e. Findability, Accessibility, Interoperability, and Reusability) of research findings. …
View article: From Theory to Practice: Demonstrators of FAIR Data Spaces Across Different Sectors
From Theory to Practice: Demonstrators of FAIR Data Spaces Across Different Sectors Open
The principles of data spaces for sovereign data exchange across trusted organizations have so far mainly been adopted in business-to-business settings, and recently scaled to cloud environments. Meanwhile, research organizations have esta…
View article: Large Language Model in Medical Informatics: Direct Classification and Enhanced Text Representations for Automatic ICD Coding
Large Language Model in Medical Informatics: Direct Classification and Enhanced Text Representations for Automatic ICD Coding Open
Addressing the complexity of accurately classifying International Classification of Diseases (ICD) codes from medical discharge summaries is challenging due to the intricate nature of medical documentation. This paper explores the use of L…
View article: BladeView: Toward Automatic Wind Turbine Inspection With Unmanned Aerial Vehicle
BladeView: Toward Automatic Wind Turbine Inspection With Unmanned Aerial Vehicle Open
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View article: A non-enhanced CT-based deep learning diagnostic system for COVID-19 infection at high risk among lung cancer patients
A non-enhanced CT-based deep learning diagnostic system for COVID-19 infection at high risk among lung cancer patients Open
Background Pneumonia and lung cancer have a mutually reinforcing relationship. Lung cancer patients are prone to contracting COVID-19, with poorer prognoses. Additionally, COVID-19 infection can impact anticancer treatments for lung cancer…
View article: YawnNet: A Visual-Centric Approach for Yawning Detection
YawnNet: A Visual-Centric Approach for Yawning Detection Open
Yawning detection is actively used in multimedia applications such as driver fatigue assessment and status monitoring. However, the accuracy and robustness of existing yawning detectors are limited due to variations in environments (especi…
View article: Falcon 7b for Software Mention Detection in Scholarly Documents
Falcon 7b for Software Mention Detection in Scholarly Documents Open
This paper aims to tackle the challenge posed by the increasing integration of software tools in research across various disciplines by investigating the application of Falcon-7b for the detection and classification of software mentions wi…
View article: Gyroscope-Assisted Motion Deblurring Network
Gyroscope-Assisted Motion Deblurring Network Open
Image research has shown substantial attention in deblurring networks in recent years. Yet, their practical usage in real-world deblurring, especially motion blur, remains limited due to the lack of pixel-aligned training triplets (backgro…
View article: FDO Manager: Minimum Viable FAIR Digital Object Implementation
FDO Manager: Minimum Viable FAIR Digital Object Implementation Open
In the digital age, data has emerged as one of the most valuable assets across various sectors, including academia, industry, and healthcare. Effective data preservation involves the management of data to ensure its long-term accessibility…
View article: Data Trading and Monetization: Challenges and Open Research Directions
Data Trading and Monetization: Challenges and Open Research Directions Open
Traditional data monetization approaches face challenges related to data protection and logistics. In response, digital data marketplaces have emerged as intermediaries simplifying data transactions. Despite the growing establishment and a…
View article: SuperEdge: Towards a Generalization Model for Self-Supervised Edge Detection
SuperEdge: Towards a Generalization Model for Self-Supervised Edge Detection Open
Edge detection is a fundamental technique in various computer vision tasks. Edges are indeed effectively delineated by pixel discontinuity and can offer reliable structural information even in textureless areas. State-of-the-art heavily re…
View article: Falcon 7b for Software Mention Detection in Scholarly Documents
Falcon 7b for Software Mention Detection in Scholarly Documents Open
This paper aims to tackle the challenge posed by the increasing integration of software tools in research across various disciplines by investigating the application of Falcon-7b for the detection and classification of software mentions wi…
View article: Data Trading and Monetization: Challenges and Open Research Directions
Data Trading and Monetization: Challenges and Open Research Directions Open
Traditional data monetization approaches face challenges related to data protection and logistics. In response, digital data marketplaces have emerged as intermediaries simplifying data transactions. Despite the growing establishment and a…
View article: Skeleton Ground Truth Extraction: Methodology, Annotation Tool and Benchmarks
Skeleton Ground Truth Extraction: Methodology, Annotation Tool and Benchmarks Open
Skeleton Ground Truth (GT) is critical to the success of supervised skeleton extraction methods, especially with the popularity of deep learning techniques. Furthermore, we see skeleton GTs used not only for training skeleton detectors wit…
View article: Beyond Trading Data: The Hidden Influence of Public Awareness and Interest on Cryptocurrency Volatility
Beyond Trading Data: The Hidden Influence of Public Awareness and Interest on Cryptocurrency Volatility Open
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View article: Skeleton Ground Truth Extraction: Methodology, Annotation Tool and Benchmarks
Skeleton Ground Truth Extraction: Methodology, Annotation Tool and Benchmarks Open
Skeleton Ground Truth (GT) is critical to the success of supervised skeleton extraction methods, especially with the popularity of deep learning techniques. Furthermore, we see skeleton GTs used not only for training skeleton detectors wit…
View article: FAIR Data Spaces - Building a Common Cloud-Based Data Space for Industry and Science by Linking Gaia-X and NFDI
FAIR Data Spaces - Building a Common Cloud-Based Data Space for Industry and Science by Linking Gaia-X and NFDI Open
This abstract was submitted and accepted to CoRDI 2023 (Conference on Research Data Infrastructure). See also the corresponding poster: https://zenodo.org/record/8409619
View article: Pedestrian Collision Prediction Using a Monocular Camera
Pedestrian Collision Prediction Using a Monocular Camera Open
Presentation slides of our paper "Pedestrian Collision Prediction Using a Monocular Camera" at the iWOAR Workshop 2023
View article: Enhancing Reproducibility in Research Through FAIR Digital Objects
Enhancing Reproducibility in Research Through FAIR Digital Objects Open
The FAIR principles were introduced to enhance data reuse by providing guidelines for effective data management practices. In the broader context of research, assets encompass not only data but also artifacts such as code, software, and pu…
View article: Knowledge guided multi-filter residual convolutional neural network for ICD coding from clinical text
Knowledge guided multi-filter residual convolutional neural network for ICD coding from clinical text Open
A common challenge encountered when using Deep Neural Network models for automatic ICD coding is their potential inability to effectively handle unseen clinical texts, especially when these models are only trained on a limited number of ex…
View article: Deep author name disambiguation using DBLP data
Deep author name disambiguation using DBLP data Open
In the academic world, the number of scientists grows every year and so does the number of authors sharing the same names. Consequently, it is challenging to assign newly published papers to their respective authors. Therefore, author name…
View article: Enhancing Data Space Semantic Interoperability through Machine Learning: a Visionary Perspective
Enhancing Data Space Semantic Interoperability through Machine Learning: a Visionary Perspective Open
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View article: Knowledge Guided Multi-filter Residual Convolutional Neural Network for ICD Coding from Clinical Text
Knowledge Guided Multi-filter Residual Convolutional Neural Network for ICD Coding from Clinical Text Open
One challenge often encountered when using Deep Neural Network models for automatic ICD coding is their potential inability to effectively handle unseen clinical texts, especially when these models are only trained on a limited number of e…