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Dynamic-SLAM: Semantic monocular visual localization and mapping based on deep learning
時間 2021-07-12
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Dynamic-SLAM: Semantic monocular visual localization and mapping based on deep learning in dynamic environment 漏檢補償算法——提高SSD的召回率 首先基於卷積神經網絡,構造一個聯合先驗知識的SSD目標檢測器,在語義層檢測新檢測線程中的動態目標;然後,針對現有SSD目標檢測網絡的召回率較低
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相關文章
1.
VLocNet++: Deep Multitask Learning for Semantic Visual Localization and Odometry 語義視覺定位與里程計
2.
閱讀《A Survey of Monocular Simultaneous Localization and Mapping》
3.
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4.
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5.
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6.
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7.
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8.
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