Research map / Vision-language and multimodal / Human and embodied modeling
How Deep is the Feature Analysis underlying Rapid Visual Categorization?
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Fine-tune VGG16 on the animal vs. non-animal task | VGG16 highest layer · Animal vs. non-animal categorization | accuracy: 95.0% -> 97.0% | Helped |
| Use higher processing stages | AlexNet, VGG16, and VGG19 · Animal vs. non-animal categorization | accuracy | Helped |
| Use deeper stages rather than intermediate stages | AlexNet, VGG16, and VGG19 · Human-model decision-score agreement | Spearman's rho | Hurt |
| Increase the maximum response time from 500 ms to 1,000 ms | Human participants · Animal vs. non-animal categorization control | accuracy: 74 % -> 84 % | Helped |
| Increase the maximum response time from 1,000 ms to 2,000 ms | Human participants · Animal vs. non-animal categorization control | accuracy: 84 % -> 84% | No clear effect |
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