中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
机构
采集方式
内容类型
发表日期
学科主题
筛选

浏览/检索结果: 共7条,第1-7条 帮助

条数/页: 排序方式:
Phytoextraction of As by Pteris vittata L. assisted with municipal sewage sludge compost and associated mechanism 期刊论文  OAI收割
SCIENCE OF THE TOTAL ENVIRONMENT, 2023, 卷号: 893, 页码: 164705
作者:  
Guo, Guanghui;  Zhang, Degang;  Lei, Mei;  Wan, Xiaoming;  Yang, Jun
  |  收藏  |  浏览/下载:103/0  |  提交时间:2023/08/22
Palladium-Catalyzed Propargylic [n+2] Cycloaddition: An Efficient Strategy for Construction of Benzo-Fused Medium-Sized Heterocycles 期刊论文  OAI收割
ADVANCED SYNTHESIS & CATALYSIS, 2019, 卷号: 361, 期号: 4, 页码: 836-841
作者:  
Liu, Zhen-Ting;  Hu, Xiang-Ping
  |  收藏  |  浏览/下载:66/0  |  提交时间:2019/06/20
Palladium-catalyzed propargylic [n+2] cycloaddition: an efficient strategy for construction of benzo-fused medium-sized heterocycles 期刊论文  iSwitch采集
Advanced synthesis & catalysis, 2019, 卷号: 361, 期号: 4, 页码: 836-841
作者:  
Liu, Zhen-Ting;  Hu, Xiang-Ping
收藏  |  浏览/下载:90/0  |  提交时间:2019/05/08
Classification of hyperspectral image based on SVM optimized by a new particle swarm optimization (EI CONFERENCE) 会议论文  OAI收割
2012 2nd International Conference on Remote Sensing, Environment and Transportation Engineering, RSETE 2012, June 1, 2012 - June 3, 2012, Nanjing, China
作者:  
Gao X.;  Yu P.;  Yu P.
收藏  |  浏览/下载:19/0  |  提交时间:2013/03/25
Support Vector Machine (SVM) is used to classify hyperspectral remote sensing image in this paper. Radial Basis Function (RBF)  which is most widely used  is chosen as the kernel function of SVM. Selection of kernel function parameter is a pivotal factor which influences the performance of SVM. For this reason  Particle Swarm Optimization (PSO) is provided to get a better result. In order to improve the optimization efficiency of kernel function parameter  firstly larger steps of grid search method is used to find the appropriate rang of parameter. Since the PSO tends to be trapped into local optimal solutions  a weight and mutation particle swam optimization algorithm was proposed  in which the weight dynamically changes with a liner rule and the global best particle mutates per iteration to optimize the parameters of RBF-SVM. At last  a 220-bands hyperspectral remote sensing image of AVIRIS is taken as an experiment  which demonstrates that the method this paper proposed is an effective way to search the SVM parameters and is available in improving the performance of SVM classifiers. 2012 IEEE.  
Efficient human action recognition using accumulated motion image and support vector machines (EI CONFERENCE) 会议论文  OAI收割
International Workshop on Advanced Computational Intelligence and Intelligent Informatics, IWACIII 2011, November 19, 2011 - November 23, 2011, Suzhou, China
作者:  
Zhang X.;  Zhang J.;  Zhang J.;  Zhang X.;  Zhang X.
收藏  |  浏览/下载:67/0  |  提交时间:2013/03/25
Vision-based human action recognition provides an advanced interface  and research in this field of human action recognition has been actively carried out. This paper describes a scheme for recognizing human actions from a video sequences. The proposed method is an extension of the Motion History Image(MHI) method based on the ordinal measure of accumulated motion  which is robust to variations of appearances. We define the accumulated motion image(AMI) using image differences firstly. Then the AMI of the video sequencesis resized to a MN regulation following the standard of training phases. Finally  we employ Support Vector Machine(SVM) as a classifier to distinguish the current activity in target video sequences. In a word  our proposed algorithm not only outperforms the state of art on public available KTH data set and Weizmann data set  but also proves practical to some real world applications  in addition  this method is computationally simple and able to achieve a satisfactory accuracy.  
Research on the affect of differential-images technique to the resolution of infrared spatial camera (EI CONFERENCE) 会议论文  OAI收割
3rd International Symposium on Advanced Optical Manufacturing and Testing Technologies: Optical Test and Measurement Technology and Equipment, July 8, 2007 - July 12, 2007, Chengdu, China
Jin G.; An Y.; Qi Y.; Hu F.
收藏  |  浏览/下载:15/0  |  提交时间:2013/03/25
The optical system of infrared spatial camera adopts bigger relative aperture and bigger pixel size on focal plane element. These make the system have bulky volume and low resolution. The potential of the optical systems can not be exerted adequately. So  one method for improving resolution of infrared spatial camera based on multi-frame difference-images is introduced in the dissertation. The method uses more than one detectors to acquire several difference images  and then reconstructs a new high-resolution image from these images through the relationship of pixel grey value. The technique of difference-images that uses more than two detectors is researched  and it can improve the resolution 2.5 times in theory. The relationship of pixel grey value between low-resolution difference-images and high-resolution image is found by analyzing the energy of CCD sampling  a general relationship between the enhanced times of the resolution of the detected figure with differential method and the least count of CCD that will be used to detect figure is given. Based on the research of theory  the implementation process of utilizing difference-images technique to improve the resolution of the figure was simulated used Matlab software by taking a personality image as the object  and the software can output the result as an image. The result gotten from the works we have finished proves that the technique is available in high-resolution image reconstruction. The resolution of infrared spatial camera can be improved evidently when holding the size of optical structure or using big size detector by applying for difference image technique. So the technique has a high value in optical remote fields.  
A method for improving the precision of motion vector estimation based on gyroscope (EI CONFERENCE) 会议论文  OAI收割
ICO20: Optical Information Processing, August 21, 2005 - August 26, 2005, Changchun, China
作者:  
Sun H.;  Sun H.;  Zhang Y.
收藏  |  浏览/下载:17/0  |  提交时间:2013/03/25