Information theoretic and machine learning approaches to quantify non-linear visual feature interaction underlying visual object recognition
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2012-07-01
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| Series: | BMC Neuroscience |
| _version_ | 1818497463385849856 |
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| author | Alemi-Neissi Alireza Baldassi Carlo Braunstein Alfredo Pagnani Andrea Zecchina Riccardo Zoccolan Davide |
| author_facet | Alemi-Neissi Alireza Baldassi Carlo Braunstein Alfredo Pagnani Andrea Zecchina Riccardo Zoccolan Davide |
| author_sort | Alemi-Neissi Alireza |
| collection | DOAJ |
| first_indexed | 2024-12-10T18:46:05Z |
| format | Article |
| id | doaj.art-99b5a312d9364487a89b011c75b8b004 |
| institution | Directory Open Access Journal |
| issn | 1471-2202 |
| language | English |
| last_indexed | 2024-12-10T18:46:05Z |
| publishDate | 2012-07-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Neuroscience |
| spelling | doaj.art-99b5a312d9364487a89b011c75b8b0042022-12-22T01:37:29ZengBMCBMC Neuroscience1471-22022012-07-0113Suppl 1P210.1186/1471-2202-13-S1-P2Information theoretic and machine learning approaches to quantify non-linear visual feature interaction underlying visual object recognitionAlemi-Neissi AlirezaBaldassi CarloBraunstein AlfredoPagnani AndreaZecchina RiccardoZoccolan Davide |
| spellingShingle | Alemi-Neissi Alireza Baldassi Carlo Braunstein Alfredo Pagnani Andrea Zecchina Riccardo Zoccolan Davide Information theoretic and machine learning approaches to quantify non-linear visual feature interaction underlying visual object recognition BMC Neuroscience |
| title | Information theoretic and machine learning approaches to quantify non-linear visual feature interaction underlying visual object recognition |
| title_full | Information theoretic and machine learning approaches to quantify non-linear visual feature interaction underlying visual object recognition |
| title_fullStr | Information theoretic and machine learning approaches to quantify non-linear visual feature interaction underlying visual object recognition |
| title_full_unstemmed | Information theoretic and machine learning approaches to quantify non-linear visual feature interaction underlying visual object recognition |
| title_short | Information theoretic and machine learning approaches to quantify non-linear visual feature interaction underlying visual object recognition |
| title_sort | information theoretic and machine learning approaches to quantify non linear visual feature interaction underlying visual object recognition |
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