Visual perception of liquids: Insights from deep neural networks.
Visually inferring material properties is crucial for many tasks, yet poses significant computational challenges for biological vision. Liquids and gels are particularly challenging due to their extreme variability and complex behaviour. We reasoned that measuring and modelling viscosity perception...
Main Authors: | Jan Jaap R van Assen, Shin'ya Nishida, Roland W Fleming |
---|---|
Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2020-08-01
|
Series: | PLoS Computational Biology |
Online Access: | https://doi.org/10.1371/journal.pcbi.1008018 |
Similar Items
-
Visual wetness perception based on image color statistics
by: Sawayama, Masataka, et al.
Published: (2017) -
S4-3: Spatial Processing of Visual Motion
by: Shin'ya Nishida
Published: (2012-10-01) -
New Insights in Machine Learning and Deep Neural Networks
Published: (2023) -
Visual Object Tracking with Deep Neural Networks
Published: (2019) -
Mislocalization of a Visual Flash in the Direction of Subsequent Auditory Motion
by: Takahiro Kawabe, et al.
Published: (2011-10-01)