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Why psychologists should embrace rather than abandon DNNs
Galit Yovel1,2, Naphtali Abudarham1
1School of Psychological Sciences, Tel Aviv University, Tel Aviv, Israel gality@tauex.tau.ac.il; https://people.socsci.tau.ac.il/mu/galityovel/ naphtool@gmail.com.
The Behavioral and Brain Sciences
|December 6, 2023
Summary
Deep neural networks (DNNs) offer advanced computational models for understanding human cognition. Studying DNN representations provides novel insights into high-level vision, crucial for psychological sciences.
Area of Science:
- Cognitive Psychology
- Computational Neuroscience
- Artificial Intelligence
Background:
- Traditional models of human cognition lack complex, high-level representations.
- Deep neural networks (DNNs) excel at generating such representations.
Purpose of the Study:
- To explore the utility of DNNs in understanding human high-level vision.
- To highlight the importance of DNNs for psychological sciences.
Main Methods:
- Analyzing high-level representations generated by DNNs.
- Comparing DNN-derived insights with traditional cognitive models.
Main Results:
- DNNs provide a powerful framework for modeling complex cognitive processes.
- Insights into human high-level vision are significantly enhanced through DNN analysis.
Conclusions:
- Deep neural networks are indispensable tools for modern psychological research.
- Further integration of DNNs is essential for advancing the study of human cognition and vision.
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