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	Biodiversity priority areas and conservation strategies for seed plants in China 期刊论文 OAI收割 FRONTIERS IN PLANT SCIENCE, 2022, 卷号: 13 作者: Yang, Xudong; Zhang, Wendi; Qin, Fei; Yu, Jianghong; Xue, Tiantian \| 收藏 \| 浏览/下载：34/0 \| 提交时间：2024/03/07 biodiversity hotspot complementary algorithm correlation analysis priority areas phylogenetic diversity species richness
	A secondary-decomposition-ensemble learning paradigm for forecasting PM2.5 concentration 期刊论文 OAI收割 ATMOSPHERIC POLLUTION RESEARCH, 2018, 卷号: 9, 期号: 6, 页码: 989-999 作者: Gan, Kai; Sun, Shaolong; Wang, Shouyang; Wei, Yunjie \| 收藏 \| 浏览/下载：58/0 \| 提交时间：2018/11/16 Secondary-decomposition-ensemble learning paradigm Complementary ensemble empirical mode decomposition Phase space reconstruction Least square support vector regression Hybrid intelligent algorithm
	Integrated intensity, orientation code and spatial information for robust tracking (EI CONFERENCE) 会议论文 OAI收割 2007 2nd IEEE Conference on Industrial Electronics and Applications, ICIEA 2007, May 23, 2007 - May 25, 2007, Harbin, China 作者: Wang Y.; Wang Y.; Wang Y.; Wang Y.; Wang Y. 收藏 \| 浏览/下载：38/0 \| 提交时间：2013/03/25 real-time tracking is an important topic in computer vision. Conventional single cue algorithms typically fail outside limited tracking conditions. Integration of multimodal visual cues with complementary failure modes allows tracking to continue despite losing individual cues. In this paper we combine intensity orientation codes and special information to form a new intensity-orientation codes-special (IOS) feature to represent the target. The intensity feature is not affected by the shape variance of object and has good stability. Orientation codes matching is robust for searching object in cluttered environments even in the cases of illumination fluctuations resulting from shadowing or highlighting etc The spatial locations of the pixels are used which allow us to take into account the spatial information which is lost in traditional histogram. Histograms of intensity orientation codes and spatial information are employed for represent the target Mean shift algorithm is a nonparametric density estimation method. The fast and optimal mode matching can be achieved by this method. In order to reduce the compute time we use the mean shift procedure to reach the target localization. Experiment results show that the new method can successfully cope with clutter partial occlusions illumination change and target variations such as scale and rotation. The computational complexity is very low. If the size of the target is 3628 pixels it only needs 12ms to complete the method. 2007 IEEE.
	Multiwavelet based multispectral image fusion for corona detection (EI CONFERENCE) 会议论文 OAI收割 ICO20: Optical Information Processing, August 21, 2005 - August 26, 2005, Changchun, China 作者: Wang X.; Yang H.-J.; Sui Y.-X.; Yan F.; Yan F. 收藏 \| 浏览/下载：42/0 \| 提交时间：2013/03/25 Image fusion refers to the integration of complementary information provided by various sensors such that the new images are more useful for human or machine perception. Multiwavelet transform has simultaneous orthogonality symmetry compact support and vanishing moment which are not possible with scalar wavelet transform. Multiwavelet analysis can offer more precise image analysis than wavelet multiresolution analysis. In this paper a new image fusion algorithm based on discrete multiwavelet transform (DMWT) to fuse the dual-spectral images generated from the corona detection system is presented. The dual-spectrum detection system is used to detect the corona and indicate its exact location. The system combines a solar-blind UV ICCD with a visible camera where the UV image is useful for detecting UV emission from corona and the visible image shows the position of the corona. The developed fusion algorithm is proposed considering the feature of the UV and visible images adequately. The source images are performed at the pixel level. First a decomposition step is taken with the DMWT. After the decomposition step a pyramid for each source image in each level can be obtained. Then an optimized coefficient fusion rule consisting of activity level measurement coefficient combining and consistency verification is used to acquire the fused coefficients. This process reduces the impulse noise of UV image. Finally a new fused image is obtained by reconstructing the fused coefficients using inverse DMWT. This image fusion algorithm has been applied to process the multispectral UV/visible images. Experimental results show that the proposed method outperforms the discrete wavelet transform based approach.