7 citations · 13 across the 7 of their papers we have counts for
4 papers · 1 filter
Class-Specific Explainability for Deep Time Series Classifiers
Ramesh Doddaiah, Prathyush Parvatharaju, Elke Rundensteiner +1
Explainability helps users trust deep learning solutions for time series classification. However, existing explainability methods for multi-class time series classifiers focus on o…
Stop&Hop: Early Classification of Irregular Time Series
Thomas Hartvigsen, Walter Gerych, Jidapa Thadajarassiri +2
Early classification algorithms help users react faster to their machine learning model's predictions. Early warning systems in hospitals, for example, let clinicians improve their…
DeepEmotex: Classifying Emotion in Text Messages using Deep Transfer Learning
Maryam Hasan, Elke Rundensteiner, Emmanuel Agu
Transfer learning has been widely used in natural language processing through deep pretrained language models, such as Bidirectional Encoder Representations from Transformers and U…
TWEET-FID: An Annotated Dataset for Multiple Foodborne Illness Detection Tasks
Ruofan Hu, Dongyu Zhang, Dandan Tao +3
Foodborne illness is a serious but preventable public health problem -- with delays in detecting the associated outbreaks resulting in productivity loss, expensive recalls, public…