50 citations · 158 across the 11 of their papers we have counts for
12 papers
Classification of Alzheimers Disease with Deep Learning on Eye-tracking Data
Harshinee Sriram, Cristina Conati, Thalia Field
Existing research has shown the potential of classifying Alzheimers Disease (AD) from eye-tracking (ET) data with classifiers that rely on task-specific engineered features. In thi…
Evaluating the overall sensitivity of saliency-based explanation methods
Harshinee Sriram, Cristina Conati
We address the need to generate faithful explanations of "black box" Deep Learning models. Several tests have been proposed to determine aspects of faithfulness of explanation meth…
GANonymization: A GAN-based Face Anonymization Framework for Preserving Emotional Expressions
Fabio Hellmann, Silvan Mertes, Mohamed Benouis +5
In recent years, the increasing availability of personal data has raised concerns regarding privacy and security. One of the critical processes to address these concerns is data an…
A Theoretical Framework for AI Models Explainability with Application in Biomedicine
Matteo Rizzo, Alberto Veneri, Andrea Albarelli +3
EXplainable Artificial Intelligence (XAI) is a vibrant research topic in the artificial intelligence community, with growing interest across methods and domains. Much has been writ…
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…
Cascading Convolutional Temporal Colour Constancy
Matteo Rizzo, Cristina Conati, Daesik Jang +1
Computational Colour Constancy (CCC) consists of estimating the colour of one or more illuminants in a scene and using them to remove unwanted chromatic distortions. Much research…