Zobrazeno 1 - 10
of 262
pro vyhledávání: '"Suominen, Hanna"'
Autor:
Simon, Emmanuel Iko-Ojo, Hettiarachchi, Chirath, Potanin, Alex, Suominen, Hanna, Fard, Fatemeh
Context: Previous studies demonstrate that Machine or Deep Learning (ML/DL) models can detect Technical Debt from source code comments called Self-Admitted Technical Debt (SATD). Despite the importance of ML/DL in software development, limited studie
Externí odkaz:
http://arxiv.org/abs/2408.10529
Autor:
Cantrill, Sam, Ahmedt-Aristizabal, David, Petersson, Lars, Suominen, Hanna, Armin, Mohammad Ali
Camera-based remote photoplethysmography (rPPG) enables contactless measurement of important physiological signals such as pulse rate (PR). However, dynamic and unconstrained subject motion introduces significant variability into the facial appearanc
Externí odkaz:
http://arxiv.org/abs/2404.09378
Autor:
Brew-Sam, Nicola, Chhabra, Madhur, Parkinson, Anne, Hannan, Kristal, Brown, Ellen, Pedley, Lachlan, Brown, Karen, Wright, Kristine, Pedley, Elizabeth, Nolan, Christopher J, Phillips, Christine, Suominen, Hanna, Tricoli, Antonio, Desborough, Jane
Publikováno v:
JMIR Diabetes, Vol 6, Iss 1, p e20973 (2021)
BackgroundIn the last decade, diabetes management has begun to transition to technology-based care, with young people being the focus of many technological advances. Yet, detailed insights into the experiences of young people and their caregivers of
Externí odkaz:
https://doaj.org/article/54d9aa7fd906403a923648967c5c7dd1
In this work, we tested the Triplet Extraction (TE) capabilities of a variety of Large Language Models (LLMs) of different sizes in the Zero- and Few-Shots settings. In detail, we proposed a pipeline that dynamically gathers contextual information fr
Externí odkaz:
http://arxiv.org/abs/2312.01954
This study aims to compare multiple deep learning-based forecasters for the task of predicting volatility using multivariate data. The paper evaluates a range of models, starting from simpler and shallower ones and progressing to deeper and more comp
Externí odkaz:
http://arxiv.org/abs/2306.12446
Autor:
Dutt, Shankar, Shao, Hancheng, Karawdeniya, Buddini, Bandara, Y. M. Nuwan D. Y., Daskalaki, Elena, Suominen, Hanna, Kluth, Patrick
Publikováno v:
Small Methods 2023, 2300676
Proteins are arguably the most important class of biomarkers for health diagnostic purposes. Label-free solid-state nanopore sensing is a versatile technique for sensing and analysing biomolecules such as proteins at single-molecule level. While mole
Externí odkaz:
http://arxiv.org/abs/2302.12098
Publikováno v:
JMIR Medical Informatics, Vol 3, Iss 2, p e19 (2015)
BackgroundOver a tenth of preventable adverse events in health care are caused by failures in information flow. These failures are tangible in clinical handover; regardless of good verbal handover, from two-thirds to all of this information is lost a
Externí odkaz:
https://doaj.org/article/86b34c6042404e13a7f9977ae6604403
The Bidirectional Encoder Representations from Transformers (BERT) model has achieved the state-of-the-art performance for many natural language processing (NLP) tasks. Yet, limited research has been contributed to studying its effectiveness when the
Externí odkaz:
http://arxiv.org/abs/2109.07243
Autor:
Vlieger, Robin, Austin, Duncan, Apthorp, Deborah, Daskalaki, Elena, Lensky, Artem, Walton-Sonda, Dianne, Suominen, Hanna, Lueck, Christian J.
Publikováno v:
In Brain Research 1 June 2024 1832
Well-annotated datasets, as shown in recent top studies, are becoming more important for researchers than ever before in supervised machine learning (ML). However, the dataset annotation process and its related human labor costs remain overlooked. In
Externí odkaz:
http://arxiv.org/abs/2108.09913