15 citations · 27 across the 15 of their papers we have counts for
16 papers
Random Initialization as a Baseline for Time Series Foundation Models
Pinar Sungu Isiacik, Georgiana Ifrim
Time series foundation models (TSFMs) use self-supervised pretraining to learn reusable representations for downstream tasks such as multivariate time series classification (MTSC).…
Revisiting WEASEL 2.0: Reproduction, Sensitivity, and an Adaptive Ensemble-Size Rule
Cian Higgins, Gerard Carrigan, Pinar Sungu Isiacik +1
WEASEL 2.0 is a dictionary-based time series classifier that combines dilated sliding windows with a randomised hyperparameter ensemble and a fixed-size dense feature representatio…
Beyond Simulated Benchmarks: Evaluating Motion Representations for Fall Detection Under Real-World Data Scarcity
Timilehin B. Aderinola, Ilaria D'Ascanio, Luca Palmerini +5
Falls are a major health concern for older adults, and wearable sensors have been widely explored for detecting falls and enabling timely intervention. However, real-world falls ar…
Scaling Time Series Classification via XAI-Driven Data Reduction
Davide Italo Serramazza, Thach Le Nguyen, Georgiana Ifrim
Explainable AI (XAI) for time series has seen significant algorithmic growth, but its utility in providing measurable performance gains for downstream tasks remains under-explored.…
Watch Your Step: A Cost-Sensitive Framework for Accelerometer-Based Fall Detection in Real-World Streaming Scenarios
Timilehin B. Aderinola, Luca Palmerini, Ilaria D'Ascanio +5
Real-time fall detection is crucial for enabling timely interventions and mitigating the severe health consequences of falls, particularly in older adults. However, existing method…
An Empirical Evaluation of Factors Affecting SHAP Explanation of Time Series Classification
Davide Italo Serramazza, Nikos Papadeas, Zahraa Abdallah +1
Explainable AI (XAI) has become an increasingly important topic for understanding and attributing the predictions made by complex Time Series Classification (TSC) models. Among att…
Improving the Evaluation and Actionability of Explanation Methods for Multivariate Time Series Classification
Davide Italo Serramazza, Thach Le Nguyen, Georgiana Ifrim
Explanation for Multivariate Time Series Classification (MTSC) is an important topic that is under explored. There are very few quantitative evaluation methodologies and even fewer…
Machine Vision-Enabled Sports Performance Analysis
Timilehin B. Aderinola, Hananeh Younesian, Cathy Goulding +3
This study investigates the feasibility of monocular 2D markerless motion capture (MMC) using a single smartphone to measure jump height, velocity, flight time, co…
Evaluating Explanation Methods for Multivariate Time Series Classification
Davide Italo Serramazza, Thu Trang Nguyen, Thach Le Nguyen +1
Multivariate time series classification is an important computational task arising in applications where data is recorded over time and over multiple channels. For example, a smart…
An Examination of Wearable Sensors and Video Data Capture for Human Exercise Classification
Ashish Singh, Antonio Bevilacqua, Timilehin B. Aderinola +5
Wearable sensors such as Inertial Measurement Units (IMUs) are often used to assess the performance of human exercise. Common approaches use handcrafted features based on domain ex…
Robust Explainer Recommendation for Time Series Classification
Thu Trang Nguyen, Thach Le Nguyen, Georgiana Ifrim
Time series classification is a task which deals with temporal sequences, a prevalent data type common in domains such as human activity recognition, sports analytics and general s…
Quantifying Jump Height Using Markerless Motion Capture with a Single Smartphone
Timilehin B. Aderinola, Hananeh Younesian, Darragh Whelan +2
Goal: The countermovement jump (CMJ) is commonly used to measure lower-body explosive power. This study evaluates how accurately markerless motion capture (MMC) with a single smart…
Classification of cow diet based on milk mid infrared spectra: a data analysis competition at the "International workshop of spectroscopy and chemometrics 2022"
Maria Frizzarin, Giulio Visentin, Alessandro Ferragina +14
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…
Fast and Robust Video-Based Exercise Classification via Body Pose Tracking and Scalable Multivariate Time Series Classifiers
Ashish Singh, Antonio Bevilacqua, Thach Le Nguyen +6
Technological advancements have spurred the usage of machine learning based applications in sports science. Physiotherapists, sports coaches and athletes actively look to incorpora…
Scalable Classifier-Agnostic Channel Selection for Multivariate Time Series Classification
Bhaskar Dhariyal, Thach Le Nguyen, Georgiana Ifrim
Accuracy is a key focus of current work in time series classification. However, speed and data reduction in many applications is equally important, especially when the data scale a…
Automated Mobility Context Detection with Inertial Signals
Antonio Bevilacqua, Lisa Alcock, Brian Caulfield +4
Remote monitoring of motor functions is a powerful approach for health assessment, especially among the elderly population or among subjects affected by pathologies that negatively…