2 citations · 4 across the 3 of their papers we have counts for
4 papers · 1 filter
Multivariate Time Series Early Classification Across Channel and Time Dimensions
Leonardos Pantiskas, Kees Verstoep, Mark Hoogendoorn +1
Nowadays, the deployment of deep learning models on edge devices for addressing real-world classification problems is becoming more prevalent. Moreover, there is a growing populari…
An Empirical Evaluation of Multivariate Time Series Classification with Input Transformation across Different Dimensions
Leonardos Pantiskas, Kees Verstoep, Mark Hoogendoorn +1
In current research, machine and deep learning solutions for the classification of temporal data are shifting from single-channel datasets (univariate) to problems with multiple ch…
Taking ROCKET on an Efficiency Mission: Multivariate Time Series Classification with LightWaveS
Leonardos Pantiskas, Kees Verstoep, Mark Hoogendoorn +1
Nowadays, with the rising number of sensors in sectors such as healthcare and industry, the problem of multivariate time series classification (MTSC) is getting increasingly releva…
A Framework for Imbalanced Time-series Forecasting
Luis P. Silvestrin, Leonardos Pantiskas, Mark Hoogendoorn
Time-series forecasting plays an important role in many domains. Boosted by the advances in Deep Learning algorithms, it has for instance been used to predict wind power for eolic…