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Self-Adaptive-Filling Deep Convolutional Neural Network Classification Method for Mountain
作者: Shiou   Li     Xianyun   Fei     Peilong   Chen     Zhen   Wang     Yajun   Gao     Kai   Cheng     Huilong   Wang     Yuanzhi   Zhang   来源: Remote Sensing 年份: 2023 文献类型 : 期刊 关键词: based   image   sensing   deep   images   vegetation   learning   type   classification   aerial   remote   mountain   high   Analysis   spatial   object  
描述: require the integration of Object-Based Image Analysis (OBIA) and Deep Convolutional Neural Networks
Self-Adaptive-Filling Deep Convolutional Neural Network Classification Method for Mountain
作者: Shiou   Li     Xianyun   Fei     Peilong   Chen     Zhen   Wang     Yajun   Gao     Kai   Cheng     Huilong   Wang     Yuanzhi   Zhang   来源: Remote Sensing 年份: 2023 文献类型 : 期刊 关键词: based   image   sensing   deep   images   vegetation   learning   type   classification   aerial   remote   mountain   high   Analysis   spatial   object  
描述: require the integration of Object-Based Image Analysis (OBIA) and Deep Convolutional Neural Networks
Hypergraph convolution mix DDPG for multi-aerial base station deployment
作者: He   Haoran     Zhou   Fanqin     Zhao   Yikun     Li   Wenjing     Feng   Lei   来源: Journal of Cloud Computing 年份: 2023 文献类型 : 期刊 关键词: Hypergraph   Agent   deep   efficiency   (AeBS)   learning   decomposition   aerial   (HGCN)   multi   (MADRL)   optimization   station   Value   convolution   reinforcement   base   energy  
描述: deep reinforcement learning (MADRL). We describe the multi-AeBS deployment challenge as a decentralized
Hypergraph convolution mix DDPG for multi-aerial base station deployment
作者: He   Haoran     Zhou   Fanqin     Zhao   Yikun     Li   Wenjing     Feng   Lei   来源: Journal of Cloud Computing 年份: 2023 文献类型 : 期刊 关键词: Hypergraph   Agent   deep   efficiency   (AeBS)   learning   decomposition   aerial   (HGCN)   multi   (MADRL)   optimization   station   Value   convolution   reinforcement   base   energy  
描述: deep reinforcement learning (MADRL). We describe the multi-AeBS deployment challenge as a decentralized
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