A York University study finds that AI vision systems lack the human-like perceptual shifts seen in biological vision during visual illusions.
Key Details
- 1York University researchers studied the motion aftereffect illusion to compare human and AI vision.
- 2Human and primate brains showed perceived shifts in object location after motion adaptation, while AI models did not.
- 3Tests combined human perception, primate visual cortex recordings, and AI neural network analysis.
- 4Findings reveal current AI systems lack history-dependent spatial representations present in biological vision.
- 5Research suggests new benchmarks for evaluating dynamic, human-compatible AI vision models.
Why It Matters
Understanding and incorporating human-like perception—including common visual illusions—into AI models is crucial for ensuring reliable, clinician-compatible medical imaging AI. This study highlights a current gap between biological and artificial vision, guiding future improvements in medical imaging systems.
Source
EurekAlert
Related News
•EurekAlert
MSKAI Unveils AI Tool for Embryo Cell Analysis and Imaging-Driven Cancer Insights
MSK researchers employ AI and advanced imaging to reveal cancer mechanisms and track embryonic development at the single-cell level.
•EurekAlert
AI-Driven Home Sensors Enable Privacy-Preserving Health Emergency Detection
Researchers have developed an AI-powered home monitoring system using radar and thermal sensors to detect health emergencies and support elderly independent living.
•EurekAlert
New Study Urges 'Green AI' Practices in Medical Imaging and Healthcare
A new review highlights the urgent need for sustainable AI practices in healthcare, with emphasis on environmental impacts from applications like medical imaging.