Dynamical Hyperparameter Optimization via Deep Reinforcement Learning in Tracking
Hyperparameters are numerical pre-sets whose values are assigned prior to the commencement of a learning process. Selecting appropriate hyperparameters is often critical for achieving satisfactory performance in many vision problems, such as deep learning-based visual object tracking. However, it is...
Ausführliche Beschreibung
Bibliographische Detailangaben
| Veröffentlicht in: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - 43(2021), 5 vom: 01. Mai, Seite 1515-1529
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| 1. Verfasser: |
Dong, Xingping
(VerfasserIn) |
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| Weitere Verfasser: |
Shen, Jianbing,
Wang, Wenguan,
Shao, Ling,
Ling, Haibin,
Porikli, Fatih |
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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 |
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