Browsing Publikasjoner fra CRIStin by Subject "Object detection"
Now showing items 1-3 of 3
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6D pose estimation for subsea intervention in turbid waters
(Peer reviewed; Journal article, 2021)Manipulation tasks on subsea instalments require extremely precise detection and localization of objects of interest. This problem is referred to as “pose estimation”. In this work, we present a framework for detecting and ... -
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 ... -
Fast and accurate convolution neural network for detecting manufacturing data
(Peer reviewed; Journal article, 2021)This article introduces a technique known as clustering with particle for object detection (CPOD) for use in smart factories. CPOD builds on regional-based methods to identify smart object data using outlier detection, ...