Now showing items 1-5 of 5

    • Data Augmentation For Text Classification Tasks 

      Tamming, Daniel (University of Waterloo, 2020-08-12)
      Thanks to increases in computing power and the growing availability of large datasets, neural networks have achieved state of the art results in many natural language process- ing (NLP) and computer vision (CV) tasks. ...
    • Improving Artificial Neural Network Models for Predicting Hourly Water Consumption 

      WANG, LI (University of Waterloo, 2018-09-26)
      Smart water meter devices are now widely installed in single family residences, allowing water consumption data to be collected at a high resolution from both the temporal and spatial perspectives. Such data allows improved ...
    • Modelling Chart Trajectories using Song Features 

      Perrie, Jonathan (University of Waterloo, 2019-08-23)
      Over the years, hit song science has been a controversial topic within music information retrieval. Researchers have debated whether an unbiased dataset can be constructed to model song performance in a meaningful way. ...
    • Predicting Short-Term Water Consumption for Multi-Family Residences 

      Medina, Irish (University of Waterloo, 2018-09-20)
      Smart water meters have been installed across Abbotsford, British Columbia, Canada, to measure the water consumption of households in the area. Using this water consumption data, we develop machine learning and deep learning ...
    • Smart-Meter Enabled Estimation and Prediction of Outdoor Residential Water Consumption 

      Platsko, Valerie (University of Waterloo, 2018-01-22)
      Smart meter technology allows frequent measurements of water consumption at a household level. This greater availability of data allows improved analysis of patterns of residential water consumption, which is important ...


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