How to construct an appropriate spatial consistent measurement is the key to improving image retrieval performance. To address this problem, this paper introduces a novel image retrieval mechanism based on the family ...How to construct an appropriate spatial consistent measurement is the key to improving image retrieval performance. To address this problem, this paper introduces a novel image retrieval mechanism based on the family filtration in object region. First, we supply an object region by selecting a rectangle in a query image such that system returns a ranked list of images that contain the same object, retrieved from the corpus based on 100 images, as a result of the first rank. To further improve retrieval performance, we add an efficient spatial consistency stage, which is named family-based spatial consistency filtration, to re-rank the results returned by the first rank. We elaborate the performance of the retrieval system by some experiments on the dataset selected from the key frames of ＂TREC Video Retrieval Evaluation 2005 （TRECVID2005）＂. The results of experiments show that the retrieval mechanism proposed by us has vast major effect on the retrieval quality. The paper also verifies the stability of the retrieval mechanism by increasing the number of images from 100 to 2000 and realizes generalized retrieval with the object outside the dataset.展开更多
基于华南地区176个国家级自动气象站资料以及1981~2020年ECMWF ERA5再分析资料,采用区域性极端事件的客观识别方法(OITREE)、合成分析等方法,本文研究了华南地区区域性极端降水事件的时空分布特征,并分析了事件偏多年及偏少年的大尺度...基于华南地区176个国家级自动气象站资料以及1981~2020年ECMWF ERA5再分析资料,采用区域性极端事件的客观识别方法(OITREE)、合成分析等方法,本文研究了华南地区区域性极端降水事件的时空分布特征,并分析了事件偏多年及偏少年的大尺度环流特征。主要结论如下:区域性极端降水事件的频次在年际尺度上的周期变化较为明显,并具有较明显的月变化特征,高发时段为5~6月;在极端强度及影响范围上,华南地区大部分区域性极端降水事件强度约130 mm d^(-1),较少事件强度超出320 mm d^(-1),且区域性极端降水事件的影响范围呈显著上升趋势(约310 km^(2)a^(-1));在事件的综合强度上,综合指数Z呈现显著的上升趋势[0.05(10 a)^(-1)],表明事件强度呈现显著增加的趋势;在大湾区及广东北部,区域性极端降水事件的累计降水及其对总降水的贡献呈显著上升趋势,而在广西南部地区,两者呈下降趋势;在事件偏多年,华南地区存在显著的西南风水汽输送及整层水汽通量强辐合的特征,而在事件偏少年,华南地区具有整层水汽通量辐合偏弱的特征;一般降水日,850 hPa上华南地区位于弱偏东南风区,区域性极端降水事件降水日,华南地区位于气旋性环流的东南部,受到明显的西南风风速大值带影响。展开更多
基金supported by National High Technology Research and Development Program of China (863 Program)(No.2007AA01Z416)National Natural Science Foundation of China (No.60773056)+1 种基金Beijing New Star Project on Science and Technology (No.2007B071)Natural Science Foundation of Liaoning Province of China (No.20052184)
文摘How to construct an appropriate spatial consistent measurement is the key to improving image retrieval performance. To address this problem, this paper introduces a novel image retrieval mechanism based on the family filtration in object region. First, we supply an object region by selecting a rectangle in a query image such that system returns a ranked list of images that contain the same object, retrieved from the corpus based on 100 images, as a result of the first rank. To further improve retrieval performance, we add an efficient spatial consistency stage, which is named family-based spatial consistency filtration, to re-rank the results returned by the first rank. We elaborate the performance of the retrieval system by some experiments on the dataset selected from the key frames of ＂TREC Video Retrieval Evaluation 2005 （TRECVID2005）＂. The results of experiments show that the retrieval mechanism proposed by us has vast major effect on the retrieval quality. The paper also verifies the stability of the retrieval mechanism by increasing the number of images from 100 to 2000 and realizes generalized retrieval with the object outside the dataset.
文摘基于华南地区176个国家级自动气象站资料以及1981~2020年ECMWF ERA5再分析资料,采用区域性极端事件的客观识别方法(OITREE)、合成分析等方法,本文研究了华南地区区域性极端降水事件的时空分布特征,并分析了事件偏多年及偏少年的大尺度环流特征。主要结论如下:区域性极端降水事件的频次在年际尺度上的周期变化较为明显,并具有较明显的月变化特征,高发时段为5~6月;在极端强度及影响范围上,华南地区大部分区域性极端降水事件强度约130 mm d^(-1),较少事件强度超出320 mm d^(-1),且区域性极端降水事件的影响范围呈显著上升趋势(约310 km^(2)a^(-1));在事件的综合强度上,综合指数Z呈现显著的上升趋势[0.05(10 a)^(-1)],表明事件强度呈现显著增加的趋势;在大湾区及广东北部,区域性极端降水事件的累计降水及其对总降水的贡献呈显著上升趋势,而在广西南部地区,两者呈下降趋势;在事件偏多年,华南地区存在显著的西南风水汽输送及整层水汽通量强辐合的特征,而在事件偏少年,华南地区具有整层水汽通量辐合偏弱的特征;一般降水日,850 hPa上华南地区位于弱偏东南风区,区域性极端降水事件降水日,华南地区位于气旋性环流的东南部,受到明显的西南风风速大值带影响。
