Deep cognitive networks : enhance deep learning by modeling human cognitive mechanism / Yan Huang, Liang Wang.
Huang, Yan.; Wang, Liang.
2023
Q325.73
Available Online

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Title Deep cognitive networks : enhance deep learning by modeling human cognitive mechanism / Yan Huang, Liang Wang.
Author Huang, Yan.
ISBN 9789819902798 (electronic bk.)
9819902797 (electronic bk.)
9819902789
9789819902781
DOI https://doi.org/10.1007/978-981-99-0279-8
Imprint Singapore : Springer, 2023.
Language English
Description 1 online resource.
Other Standard Identifiers 10.1007/978-981-99-0279-8 doi
Call Number Q325.73
Dewey Decimal Classification 006.3/1
Summary Although deep learning models have achieved great progress in vision, speech, language, planning, control, and many other areas, there still exists a large performance gap between deep learning models and the human cognitive system. Many researchers argue that one of the major reasons accounting for the performance gap is that deep learning models and the human cognitive system process visual information in very different ways. To mimic the performance gap, since 2014, there has been a trend to model various cognitive mechanisms from cognitive neuroscience, e.g., attention, memory, reasoning, and decision, based on deep learning models. This book unifies these new kinds of deep learning models and calls them deep cognitive networks, which model various human cognitive mechanisms based on deep learning models. As a result, various cognitive functions are implemented, e.g., selective extraction, knowledge reuse, and problem solving, for more effective information processing. This book first summarizes existing evidence of human cognitive mechanism modeling from cognitive psychology and proposes a general framework of deep cognitive networks that jointly considers multiple cognitive mechanisms. Then, it analyzes related works and focuses primarily but not exclusively, on the taxonomy of four key cognitive mechanisms (i.e., attention, memory, reasoning, and decision) surrounding deep cognitive networks. Finally, this book studies two representative cases of applying deep cognitive networks to the task of image-text matching and discusses important future directions.
Bibliography, etc. Note Includes bibliographical references.
Access Note Access limited to authorized users.
Source of Description Online resource; title from PDF title page (SpringerLink, viewed April 7, 2023).
Added Author Wang, Liang.
Series SpringerBriefs in computer science.
Available in Other Form Print version: 9789819902781
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Chapter 1. Introduction
Chapter 2. General Framework
Chapter 3. Attention-based DCNs
Chapter 4. Memory-based DCNs
Chapter 5. Reasoning-based DCNs
Chapter 6. Decision-based DCNs
Chapter 7. Conclusions and Future Trends.

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