3 citations · 9 across the 3 of their papers we have counts for
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cs.CV2022★ 3 cited
Evaluating the Faithfulness of Saliency-based Explanations for Deep Learning Models for Temporal Colour Constancy
Matteo Rizzo, Cristina Conati, Daesik Jang +1
The opacity of deep learning models constrains their debugging and improvement. Augmenting deep models with saliency-based strategies, such as attention, has been claimed to help g…
cs.CV2020
A Neural Architecture for Detecting Confusion in Eye-tracking Data
Shane Sims, Cristina Conati
Encouraged by the success of deep learning in a variety of domains, we investigate a novel application of its methods on the effectiveness of detecting user confusion in eye-tracki…
cs.CV2019★ 3 cited
Predicting Confusion from Eye-Tracking Data with Recurrent Neural Networks
Shane D. Sims, Vanessa Putnam, Cristina Conati
Encouraged by the success of deep learning in a variety of domains, we investigate the suitability and effectiveness of Recurrent Neural Networks (RNNs) in a domain where deep lear…