Mining Interpretable AOG Representations From Convolutional Networks via Active Question Answering
In this paper, we present a method to mine object-part patterns from conv-layers of a pre-trained convolutional neural network (CNN). The mined object-part patterns are organized by an And-Or graph (AOG). This interpretable AOG representation consists of a four-layer semantic hierarchy, i.e., semant...
Ausführliche Beschreibung
Bibliographische Detailangaben
| Veröffentlicht in: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - 43(2021), 11 vom: 12. Nov., Seite 3949-3963
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| 1. Verfasser: |
Zhang, Quanshi
(VerfasserIn) |
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| Weitere Verfasser: |
Ren, Jie,
Huang, Ge,
Cao, Ruiming,
Wu, Ying Nian,
Zhu, Song-Chun |
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| Format: | Online-Aufsatz
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| Sprache: | English |
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| Veröffentlicht: |
2021
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on pattern analysis and machine intelligence
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| Schlagworte: | Journal Article
Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S. |
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