DeFusionNET : Defocus Blur Detection via Recurrently Fusing and Refining Discriminative Multi-Scale Deep Features
Albeit great success has been achieved in image defocus blur detection, there are still several unsolved challenges, e.g., interference of background clutter, scale sensitivity and missing boundary details of blur regions. To deal with these issues, we propose a deep neural network which recurrently...
Ausführliche Beschreibung
Bibliographische Detailangaben
| Veröffentlicht in: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - 44(2022), 2 vom: 04. Feb., Seite 955-968
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| 1. Verfasser: |
Tang, Chang
(VerfasserIn) |
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| Weitere Verfasser: |
Liu, Xinwang,
Zheng, Xiao,
Li, Wanqing,
Xiong, Jian,
Wang, Lizhe,
Zomaya, Albert Y,
Longo, Antonella |
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| Format: | Online-Aufsatz
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| Sprache: | English |
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| Veröffentlicht: |
2022
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on pattern analysis and machine intelligence
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| Schlagworte: | Journal Article |
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