Integrating Computational and Neural Findings in Visual Object Perception
Overview & Synopsis
The articles in this Research Topic provide a state-of-the-art overview of the current progress in integrating computational and empirical research on visual object recognition. Developments in this exciting multidisciplinary field have recently gained momentum: High performance computing enabled breakthroughs in computer vision and computational neuroscience. In parallel, innovative machine learning applications have recently become available for datamining the large-scale, high resolution brain data acquired with (ultra-high field) fMRI and dense multi-unit recordings. Finally, new techniques to integrate such rich simulated and empirical datasets for direct model testing could aid the development of a comprehensive brain model. We hope that this Research Topic contributes to these encouraging advances and inspires future research avenues in computational and empirical neuroscience.
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Document Information
| Document Title | Integrating Computational and Neural Findings in Visual Object Perception |
|---|---|
| Author / Organization | Hans P. Op de Beeck, Judith C. Peters, Rainer Goebel |
| Subject & Discipline | RC321-571 |
| Categories | Open Access Books |
| Publication Year | 2021 |
| License / Rights | Open Access / Creative Commons |
| Resource Verification | Listed PDF (Verification Pending) |
| Original Host Website |
Directory of Open Access Books
(www.doabooks.org)
|
| File Format | application/pdf (Portable Document Format) |
| Language | EN |
| Catalog ID | DOC-44659 |
| Original Source Link | Visit Source Page on www.doabooks.org » |