Browsing Publikasjoner fra CRIStin by Subject "XAI"
Now showing items 1-3 of 3
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Applying Object Detection to Marine Data and Exploring Explainability of a Fully Convolutional Neural Network Using Principal Component Analysis
(Peer reviewed; Journal article, 2021)With the rise of focus on man made changes to our planet and wildlife therein, more and more emphasis is put on sustainable and responsible gathering of resources. In an effort to preserve maritime wildlife the Norwegian ... -
Deep learning for prediction of depressive symptoms in a large textual dataset
(Peer reviewed; Journal article, 2021)Depression is a common illness worldwide with potentially severe implications. Early identification of depressive symptoms is a crucial first step towards assessment, intervention, and relapse prevention. With an increase ... -
When explainable AI meets IoT applications for supervised learning
(Peer reviewed; Journal article, 2022)This paper introduces a novel and complete framework for solving different Internet of Things (IoT) applications, which explores eXplainable AI (XAI), deep learning, and evolutionary computation. The IoT data coming from ...