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	High-level rather than low-level warming destabilizes plant community biomass production 期刊论文 OAI收割 JOURNAL OF ECOLOGY, 2021, 页码: 11 作者: Quan, Quan; Zhang, Fangyue; Jiang, Lin; Chen, Han Y. H.; Wang, Jinsong \| 收藏 \| 浏览/下载：24/0 \| 提交时间：2021/03/15 alpine meadow community biomass stability compensatory effect dominant species ecosystem function and services mean-variance scaling species diversity warming
	High-level rather than low-level warming destabilizes plant community biomass production 期刊论文 OAI收割 JOURNAL OF ECOLOGY, 2021, 页码: 11 作者: Quan, Quan; Zhang, Fangyue; Jiang, Lin; Chen, Han Y. H.; Wang, Jinsong \| 收藏 \| 浏览/下载：18/0 \| 提交时间：2021/03/15 alpine meadow community biomass stability compensatory effect dominant species ecosystem function and services mean-variance scaling species diversity warming
	Analysis on the influence of random vibration on MEMS gyro precision and error compensation (EI CONFERENCE) 会议论文 OAI收割 2011 3rd International Conference on Mechanical and Electronics Engineering, ICMEE 2011, September 23, 2011 - September 25, 2011, Hefei, China 作者: Li M. 收藏 \| 浏览/下载：24/0 \| 提交时间：2013/03/25 In order to improve its precision in dynamic environment a Kalman filter was designed. Firstly two sets of random drift data of MEMS gyro were respectively analysed and it was found that the variance of random drift under random vibration significantly increased and its mean also changed. Then calculation results show that attitude angle error under random vibration is 2.6 while in the static test it is 0.25. Analysis on the characteristics of random drift was carried out and it is found that it can be treated as stable normally distributed random signal. Finally a corresponding Kalman filter was designed. The results indicated that after filtering the variance of random drift is reduced to 0.0282 26.4% of pre-filtering and the attitude angle error is reduced to 1.5 57.7% of pre-filtering. The above method can effectively compensate for the attitude angle error of MEMS gyro caused by random vibration. This study can be a reference to the application of low-cost MEMS gyro in aircraft navigation. (2012) Trans Tech Publications Switzerland.
	Adaptive Wiener filtering with Gaussian fitted point spread function in image restoration (EI CONFERENCE) 会议论文 OAI收割 2011 IEEE 2nd International Conference on Software Engineering and Service Science, ICSESS 2011, July 15, 2011 - July 17, 2011, Beijing, China 作者: Yang L.; Zhang X.; Zhang X.; Zhang X.; Yang L. 收藏 \| 浏览/下载：44/0 \| 提交时间：2013/03/25 In the imaging process of the space remote sensing camera there was degradation phenomenon in the acquired images. In order to reduce the image blur caused by the degradation the remote sensing images were restored to give prominence to the characteristic objects in the images. First the frequency-domain notch filter was adopted to remove strip noises in the images. Then using the ground characters with the knife-edge shape in the images the point spread function of the imaging system was estimated. In order to improve the accuracy the estimated point spread function was corrected with Gaussian fitting method. Finally the images were restored using the adaptive Wiener filtering with the fitted point spread function. Experimental results of the real remote sensing images showed that almost all strip noises in the images were eliminated. After the denoised images were restored its variance and its gray mean gradient increased also its laplacian gradient increased. Restoration with Gaussian fitted point spread function is beneficial to interpreting and analyzing the remote sensing images. After restoration the blur phenomenon of the images is reduced. The characters are highlighted and the visual effect of the images is clearer. 2011 IEEE.
	Adaptive deformation estimation of moving target by weight image analysis (EI CONFERENCE) 会议论文 OAI收割 2010 2nd International Conference on Future Computer and Communication, ICFCC 2010, May 21, 2010 - May 24, 2010, Wuhan, China Bai X.-G.; Dai M. 收藏 \| 浏览/下载：27/0 \| 提交时间：2013/03/25 An algorithm based on weight image analysis is proposed for adaptive deformation estimation of moving target in mean-shift tracking method. At the first we get the weight image from the target candidate region. Then we analyze the differences between the object and background. According to that the area estimation of the target can be converted into the image segmentation task. To realize the adaptive segmentation and estimation we define the threshold as the maximum variance between object and background. Combining the estimated area and covariance matrix we can estimate the width height and orientation of the object. The experimental results on three representative video sequences validate its robustness to the deformable estimation of the targets. 2010 IEEE.
	Remote sensing image restoration using estimated point spread function (EI CONFERENCE) 会议论文 OAI收割 2010 International Conference on Information, Networking and Automation, ICINA 2010, October 17, 2010 - October 19, 2010, Kunming, China 作者: Yang L.; Yang L. 收藏 \| 浏览/下载：33/0 \| 提交时间：2013/03/25 In order to reduce image blur caused by the degradation phenomenon in the imaging process the acquired images of the space remote sensing camera are restored. First the frequency-domain notch filter is adopted to remove strip noises in the images. Then degradation function which is referred to as the point spread function (PSF) of the imaging system is estimated using the knife-edge method. To improve the accuracy of the estimation the estimated PSF is adjusted with Gaussian fitting. Finally the images are restored by Wiener filtering with the fitted PSF. The restoration results of the remote sensing images show that almost all strip noises are eliminated by the notch filter. After denoising and restoration the variance of the remote sensing image worked with in this paper increases 30.979 and the gray mean gradient increases 3.312. Due to Gaussian fitting the accuracy of the PSF estimation is heightened. Image restoration with the final PSF is benefit to interpreting and analyzing the remote sensing images. After restoration the contrasts of the restored images are increased and the visual effects become clearer. 2010 IEEE.
	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：28/0 \| 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.
	Measuring the system gain of the TDI CCD remote sensing camera (EI CONFERENCE) 会议论文 OAI收割 Advanced Materials and Devices for Sensing and Imaging II, November 8, 2004 - November 10, 2004, Beijing, China Ya-xia L.; Hai-ming B.; Jie L.; Jin R.; Zhi-hang H. 收藏 \| 浏览/下载：62/0 \| 提交时间：2013/03/25 The gain of a TDI CCD camera is the conversion between the number of electrons recorded by the TDI CCD and the number of digital units (counts) contained in the CCD image"[1]. TDI CCD camera has been a main technical approach for meeting the requirements of high-resolution and lightweight of remote sensing equipment. It is useful to know this conversion for evaluating the performance of the TDI CCD camera. In general a lower gain is better. However the resulting slope is the gain of the TDI CCD. We did the experiments using the Integration Sphere in order to get a flat field effects. We calculated the gain of the four IT-EI-2048 TDI CCD. The results and figures of the four TDI CCD are given. this is only true as long as the total well depth (number of electrons that a pixel can hold) of the pixels can be represented. High gains result in higher digitization noise. System gains are designed to be a compromise between the extremes of high digitization noise and loss of well depth. In this paper the mathematical theory is given behind the gain calculation on a TDI CCD camera and shows how the mathematics suggests ways to measure the gain accurately according to the Axiom Tech. The gains were computed using the mean-variance method also known as the method of photon transfer curves. This method uses the effect of quantization on the variance in the measured counts over a uniformly illuminated patch of the detector. This derivation uses the concepts of signal and noise. A linear fit is done of variance vs. mean
	基于子结构的植物功能结构随机模型学位论文 OAI收割工学博士, 中国科学院自动化研究所: 中国科学院研究生院, 2003 作者: 康孟珍收藏 \| 浏览/下载：83/0 \| 提交时间：2015/09/02 植物模型功能结构模型随机过程子结构快速算法概率泰勒级数递归 Plant model Functional structural model stochastic process substructure fast algorithm mean and variance probability Taylor