1 code implementation • 18 Dec 2023 • Timilehin B. Aderinola, Hananeh Younesian, Cathy Goulding, Darragh Whelan, Brian Caulfield, Georgiana Ifrim
$\textbf{Goal:}$ This study investigates the feasibility of monocular 2D markerless motion capture (MMC) using a single smartphone to measure jump height, velocity, flight time, contact time, and range of motion (ROM) during motor tasks.
1 code implementation • Advanced Analytics and Learning on Temporal Data 2023 • Arik Ermshaus, Patrick Schäfer, Anthony Bagnall, Thomas Guyet, Georgiana Ifrim, Vincent Lemaire, Ulf Leser, Colin Leverger, Simon Malinowski
Despite its importance, existing methods demonstrate limited efficacy on real-world multivariate time series data.
1 code implementation • 29 Aug 2023 • Davide Italo Serramazza, Thu Trang Nguyen, Thach Le Nguyen, Georgiana Ifrim
In many applications classification alone is not enough, we often need to classify but also understand what the model learns (e. g., why was a prediction given, based on what information in the data).
1 code implementation • 15 Aug 2023 • Bhaskar Dhariyal, Thach Le Nguyen, Georgiana Ifrim
The state-of-the-art in time series classification has come a long way, from the 1NN-DTW algorithm to the ROCKET family of classifiers.
no code implementations • 10 Jul 2023 • Ashish Singh, Antonio Bevilacqua, Timilehin B. Aderinola, Thach Le Nguyen, Darragh Whelan, Martin O'Reilly, Brian Caulfield, Georgiana Ifrim
Additionally, a minimum of 3 IMUs are required to outperform a single camera.
1 code implementation • 8 Jun 2023 • Thu Trang Nguyen, Thach Le Nguyen, Georgiana Ifrim
This paper provides a framework to quantitatively evaluate and rank explanation methods for time series classification.
no code implementations • 21 Feb 2023 • Timilehin B. Aderinola, Hananeh Younesian, Darragh Whelan, Brian Caulfield, Georgiana Ifrim
This study evaluates how accurately markerless motion capture (MMC) with a single smartphone can measure bilateral and unilateral CMJ jump height.
1 code implementation • 10 Oct 2022 • Maria Frizzarin, Giulio Visentin, Alessandro Ferragina, Elena Hayes, Antonio Bevilacqua, Bhaskar Dhariyal, Katarina Domijan, Hussain Khan, Georgiana Ifrim, Thach Le Nguyen, Joe Meagher, Laura Menchetti, Ashish Singh, Suzy Whoriskey, Robert Williamson, Martina Zappaterra, Alessandro Casa
In April 2022, the Vistamilk SFI Research Centre organized the second edition of the "International Workshop on Spectroscopy and Chemometrics - Applications in Food and Agriculture".
1 code implementation • 2 Oct 2022 • Ashish Singh, Antonio Bevilacqua, Thach Le Nguyen, Feiyan Hu, Kevin McGuinness, Martin OReilly, Darragh Whelan, Brian Caulfield, Georgiana Ifrim
We analyze the accuracy and robustness of BodyMTS and show that it is robust to different types of noise caused by either video quality or pose estimation factors.
1 code implementation • 18 Jun 2022 • Bhaskar Dhariyal, Thach Le Nguyen, Georgiana Ifrim
Channel selection is applied as a pre-processing step before training state-of-the-art MTSC algorithms and saves about 70\% of computation time and data storage, with preserved accuracy.
1 code implementation • ACL 2022 • Demian Gholipour Ghalandari, Chris Hokamp, Georgiana Ifrim
Sentence compression reduces the length of text by removing non-essential content while preserving important facts and grammaticality.
no code implementations • 16 May 2022 • Antonio Bevilacqua, Lisa Alcock, Brian Caulfield, Eran Gazit, Clint Hansen, Neil Ireson, Georgiana Ifrim
We explore two different approaches to this task: (1) using gait descriptors and features extracted from the input inertial signals sampled during walking episodes, together with classic machine learning algorithms, and (2) treating the input inertial signals as time series data and leveraging end-to-end state-of-the-art time series classifiers.
1 code implementation • 2 Sep 2021 • Thach Le Nguyen, Georgiana Ifrim
The key idea is to transform numerical time series to symbolic representations in the time or frequency domain, i. e., sequences of symbols, and then extract features from these sequences.
1 code implementation • 5 Jul 2021 • Maria Frizzarin, Antonio Bevilacqua, Bhaskar Dhariyal, Katarina Domijan, Federico Ferraccioli, Elena Hayes, Georgiana Ifrim, Agnieszka Konkolewska, Thach Le Nguyen, Uche Mbaka, Giovanna Ranzato, Ashish Singh, Marco Stefanucci, Alessandro Casa
A chemometric data analysis challenge has been arranged during the first edition of the "International Workshop on Spectroscopy and Chemometrics", organized by the Vistamilk SFI Research Centre and held online in April 2021.
no code implementations • 15 Mar 2021 • Adrianna Janik, Jonathan Dodd, Georgiana Ifrim, Kris Sankaran, Kathleen Curran
In previous studies, the base method is applied to the classification of cardiac disease and provides clinically meaningful explanations for the predictions of a black-box deep learning classifier.
no code implementations • 25 Jun 2020 • Severin Gsponer, Luca Costabello, Chan Le Van, Sumit Pai, Christophe Gueret, Georgiana Ifrim, Freddy Lecue
Sequence classification is the supervised learning task of building models that predict class labels of unseen sequences of symbols.
1 code implementation • 31 May 2020 • Thach Le Nguyen, Severin Gsponer, Iulia Ilie, Martin O'Reilly, Georgiana Ifrim
In this paper we propose new time series classification algorithms to address these gaps.
1 code implementation • ACL 2020 • Demian Gholipour Ghalandari, Georgiana Ifrim
Previous work on automatic news timeline summarization (TLS) leaves an unclear picture about how this task can generally be approached and how well it is currently solved.
1 code implementation • ACL 2020 • Demian Gholipour Ghalandari, Chris Hokamp, Nghia The Pham, John Glover, Georgiana Ifrim
Multi-document summarization (MDS) aims to compress the content in large document collections into short summaries and has important applications in story clustering for newsfeeds, presentation of search results, and timeline generation.
no code implementations • 16 Aug 2018 • Bichen Shi, Thanh-Binh Le, Neil Hurley, Georgiana Ifrim
This is particularly the case for local news stories that are easily over shadowed by other trending stories, and for complex news stories with ambiguous content in noisy stream environments.
1 code implementation • 12 Aug 2018 • Thach Le Nguyen, Severin Gsponer, Iulia Ilie, Georgiana Ifrim
In this work we analyse the state-of-the-art for time series classification, and propose new algorithms that aim to maintain the classifier accuracy and efficiency, but keep interpretability as a key design constraint.
no code implementations • 23 Mar 2015 • Bichen Shi, Michel Schellekens, Georgiana Ifrim
Smoothed analysis is a framework for analyzing the complexity of an algorithm, acting as a bridge between average and worst-case behaviour.