4 citations · 11 across the 5 of their papers we have counts for
5 papers
Stop overkilling simple tasks with black-box models and use transparent models instead
Matteo Rizzo, Matteo Marcuzzo, Alessandro Zangari +2
In recent years, the employment of deep learning methods has led to several significant breakthroughs in artificial intelligence. Different from traditional machine learning models…
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…
Fruit Ripeness Classification: a Survey
Matteo Rizzo, Matteo Marcuzzo, Alessandro Zangari +2
Fruit is a key crop in worldwide agriculture feeding millions of people. The standard supply chain of fruit products involves quality checks to guarantee freshness, taste, and, mos…
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…