Browsing Engineering (Faculty of) by Subject "explainable AI"
Now showing items 1-4 of 4
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Class Based Strategies for Understanding Neural Networks
(University of Waterloo, 2020-02-07)One of the main challenges for broad adoption of deep learning based models such as Convolutional Neural Networks (CNN), is the lack of understanding of their decisions. In many applications, a simpler, less capable model ... -
Diabetic retinopathy grading with respect to the segmented lesions
(University of Waterloo, 2022-05-19)One of the leading causes of irreversible vision loss is Diabetic Retinopathy (DR). The International Clinical Diabetic Retinopathy scale (ICDRS) provides grading criteria for DR. Deep Convolutional Neural Networks (DCNNs) ... -
Towards Explainable Generative Adversarial Networks
(University of Waterloo, 2022-05-09)As Generative Adversarial Networks become more and more popular for sample generation, the demand for human interpretable explanations have also skyrocketed. With the rising popularity of Generative Adversarial Networks ... -
XC: Exploring Quantitative Use Cases for Explanations in 3D Object Detection
(University of Waterloo, 2022-01-18)Explainable AI (XAI) methods are frequently applied to obtain qualitative insights about deep models' predictions. However, such insights need to be interpreted by a human observer to be useful. In this thesis, we aim to ...