Tag: machine learning

Can unsupervised deep learning models compete with their supervised counterparts for visual defect detection while meeting the high safety standards of industrial quality assurance? The short answer is "yes, they can" as we could demonstrate in a recent study published in Computers & Industrial ...

I am pleased to announce that a study was recently published in Information Systems and e-Business Management that still dates back to the time and theme of my doctoral thesis. The short summary offers some insights about the main content: "Taxonomies can serve as a valuable tool to capture dimen...

Supervised machine learning methods for image analysis require large amounts of labelled training data to solve computer vision problems. The recent rise of deep learning algorithms for recognizing image content has led to the emergence of many ad-hoc labelling tools. For this reason, together wi...

Artificial intelligence technology has started to shape how decisions are being taken and how intelligent information systems are being implemented today. However, artificial intelligence should not be considered as an abstract system property, but researchers and practitioners must also understand ...

We present labelCloud, a lightweight domain-independent labeling tool for smooth interaction in 3D point clouds to support users in generating training data for 3D object detection and 6D pose estimation.