12 citations · 13 across the 12 of their papers we have counts for
4 papers · 1 filter
Investigating the Gestalt Principle of Closure in Deep Convolutional Neural Networks
Yuyan Zhang, Derya Soydaner, Fatemeh Behrad +2
Deep neural networks perform well in object recognition, but do they perceive objects like humans? This study investigates the Gestalt principle of closure in convolutional neural…
BackFlip: The Impact of Local and Global Data Augmentations on Artistic Image Aesthetic Assessment
Ombretta Strafforello, Gonzalo Muradas Odriozola, Fatemeh Behrad +4
Assessing the aesthetic quality of artistic images presents unique challenges due to the subjective nature of aesthetics and the complex visual characteristics inherent to artworks…
Finding Closure: A Closer Look at the Gestalt Law of Closure in Convolutional Neural Networks
Yuyan Zhang, Derya Soydaner, Lisa Koßmann +2
The human brain has an inherent ability to fill in gaps to perceive figures as complete wholes, even when parts are missing or fragmented. This phenomenon is known as Closure in ps…
A toolbox for calculating objective image properties in aesthetics research
Christoph Redies, Ralf Bartho, Lisa Koßmann +4
Over the past two decades, researchers in the field of visual aesthetics have studied numerous quantitative (objective) image properties and how they relate to visual aesthetic app…