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20202026
most citedMachine Learning Processes as Sources of Ambiguity: Insights from AI Art

37 citations · 139 across the 18 of their papers we have counts for

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Showing 2024Show all

5 papers · 1 filter

cs.CV2024

LayerShuffle: Enhancing Robustness in Vision Transformers by Randomizing Layer Execution Order

Matthias Freiberger, Peter Kun, Anders Sundnes Løvlie +1

Due to their architecture and how they are trained, artificial neural networks are typically not robust toward pruning or shuffling layers at test time. However, such properties wo…

cs.HC2024★ 7 cited

AI-generated art perceptions with GenFrame -- an image-generating picture frame

Peter Kun, Matthias Freiberger, Anders Sundnes Løvlie +1

Image-generation models are changing how we express ourselves in visual art. However, what people think of AI-generated art is still largely unexplored, especially compared to trad…

cs.HC2024

Using Tangible Interaction to Design Musicking Artifacts for Non-musicians

Lucía Montesinos, Halfdan Hauch Jensen, Anders Sundnes Løvlie

This paper presents a Research through Design exploration of the potential for using tangible interactions to enable active music experiences - musicking - for non-musicians. We pr…

cs.HC2024★ 21 cited

Algorithmic Ways of Seeing: Using Object Detection to Facilitate Art Exploration

Louie Søs Meyer, Johanne Engel Aaen, Anitamalina Regitse Tranberg +4

This Research through Design paper explores how object detection may be applied to a large digital art museum collection to facilitate new ways of encountering and experiencing art…

cs.HC2024★ 37 cited

Machine Learning Processes as Sources of Ambiguity: Insights from AI Art

Christian Sivertsen, Guido Salimbeni, Anders Sundnes Løvlie +2

Ongoing efforts to turn Machine Learning (ML) into a design material have encountered limited success. This paper examines the burgeoning area of AI art to understand how artists i…