activity
20182020
most citedTime series classification for varying length series

19 citations · 19 across the 2 of their papers we have counts for

collaborators

5 papers

cs.LG2020

Time Series Extrinsic Regression

Chang Wei Tan, Christoph Bergmeir, Francois Petitjean +1

This paper studies Time Series Extrinsic Regression (TSER): a regression task of which the aim is to learn the relationship between a time series and a continuous scalar variable;…

cs.LG2020

Monash University, UEA, UCR Time Series Extrinsic Regression Archive

Chang Wei Tan, Christoph Bergmeir, Francois Petitjean +1

Time series research has gathered lots of interests in the last decade, especially for Time Series Classification (TSC) and Time Series Forecasting (TSF). Research in TSC has great…

eess.SP2020

Detecting Driver's Distraction using Long-term Recurrent Convolutional Network

Chang Wei Tan, Mahsa Salehi, Geoffrey Mackellar

In this study we demonstrate a novel Brain Computer Interface (BCI) approach to detect driver distraction events to improve road safety. We use a commercial wireless headset that g…

cs.LG201919 cited

Time series classification for varying length series

Chang Wei Tan, Francois Petitjean, Eamonn Keogh +1

Research into time series classification has tended to focus on the case of series of uniform length. However, it is common for real-world time series data to have unequal lengths.…

cs.LG2018

Elastic bands across the path: A new framework and methods to lower bound DTW

Chang Wei Tan, Francois Petitjean, Geoffrey I. Webb

There has been renewed recent interest in developing effective lower bounds for Dynamic Time Warping (DTW) distance between time series. These have many applications in time series…