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1
Introduction
2
Representations in the brain
3
The visual system
4
Visual system vs deep networks
5
Mental rotation
6
Natural objects
7
Question
8
Visual Transformer
9
Results
10
Failure mode
11
Results with humans
12
What happens in the brain
13
The model
14
Test results
15
Equivalence
16
Motivation
17
FMRI data
18
Questions
19
Recurrence
20
Future work
Description:
Explore the fascinating intersection of neuroscience and deep learning in this 49-minute lecture on modelling mental rotation in the brain. Delve into the human ability to mentally manipulate 2D and 3D object representations, a skill that deep networks currently lack. Examine ongoing research efforts to understand brain processes during mental rotation and how similar operations could be implemented in deep learning systems. Learn about the differences between the human visual system and deep networks, particularly in recognizing objects from unusual viewpoints. Discover insights from fMRI data, visual transformers, and comparative studies between humans and AI models. Gain valuable knowledge about representations in the brain, the visual system, and potential future developments in this field from Stephane Deny, an assistant professor at Aalto University with expertise in computational neuroscience and machine learning.

Modelling Mental Rotation in the Brain Using Deep Learning

Finnish Center for Artificial Intelligence FCAI
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