Exploring how humans recognize objects in complex images
Towards a Compositional Generative Model of Human Vision
['FUNDING_R01'] · UNIVERSITY OF MINNESOTA · NIH-10458624
This study is exploring how we recognize objects in complicated pictures, using advanced computer models to learn how our brains process images, which could help improve treatments for people with vision problems.
Quick facts
| Phase | ['FUNDING_R01'] |
|---|---|
| Study type | Nih_funding |
| Sex | All |
| Sponsor | UNIVERSITY OF MINNESOTA (nih funded) |
| Locations | 1 site (MINNEAPOLIS, UNITED STATES) |
| Trial ID | NIH-10458624 on ClinicalTrials.gov |
What this research studies
This research investigates the mechanisms behind human object recognition, particularly in complex natural images. By utilizing advanced Deep Convolutional Neural Networks (DCNNs), the study aims to understand how humans leverage knowledge about the structure of images and objects to enhance recognition. The approach combines computational models with insights from human perception, focusing on how hierarchical and bidirectional processing contributes to recognizing parts and whole objects. Patients may benefit from insights that could improve treatments for visual perception disorders.
Who could benefit from this research
Good fit: Ideal candidates include individuals experiencing difficulties with object recognition or visual perception.
Not a fit: Patients with no visual perception issues or those not experiencing object recognition difficulties may not benefit from this research.
Why it matters
Potential benefit: If successful, this research could lead to improved understanding and treatment of visual perception disorders.
How similar studies have performed: Other research has shown success in using computational models to understand visual perception, indicating a promising approach.
Where this research is happening
MINNEAPOLIS, UNITED STATES
- UNIVERSITY OF MINNESOTA — MINNEAPOLIS, UNITED STATES (ACTIVE)
Researchers
- Principal investigator: KERSTEN, DANIEL J — UNIVERSITY OF MINNESOTA
- Study coordinator: KERSTEN, DANIEL J
About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page below.