机构

• 自动化研究所 [2]
• 地理科学与资源研究所 [1]
• 长春光学精密机械与物... [1]

采集方式

• OAI收割 [4]

内容类型

• SCI/SSCI论文 [1]
• 会议论文 [1]
• 学位论文 [1]
• 期刊论文 [1]

发表日期

• 2022 [1]
• 2016 [1]
• 2013 [1]
• 2008 [1]

学科主题

筛选

浏览/检索结果: 共4条，第1-4条 帮助 条数/页： 5101520253035404550556065707580859095100 排序方式： 请选择题名升序题名降序提交时间升序提交时间降序作者升序作者降序发表日期升序发表日期降序 Scattered Points Interpolation with Globally Smooth B-Spline Surface using Iterative Knot Insertion 期刊论文  OAI收割 COMPUTER-AIDED DESIGN, 2022, 卷号: 148, 页码: 17 作者:  Jiang, Xin;  Wang, Bolun;  Huo, Guanying;  Su, Cheng;  Yan, Dong-Ming   |  收藏  |  浏览/下载：37/0  |  提交时间：2022/07/25 B-spline surface  Scattered data points interpolation  Knot vector construction  Fairing energy minimization   Estimation of river pollution source using the space-time radial basis collocation method SCI/SSCI论文  OAI收割 2016 作者:  Li Z.;  Mao, X. Z.;  Li, T. S.;  Zhang, S. Y.   |  收藏  |  浏览/下载：28/0  |  提交时间：2017/11/09 Contaminant source identification  Global space-time collocation model  K-fold cross-validation  Inverse problem  Radial basis function  partial-differential-equations  basis function interpolation  contaminant source location  source identification  scattered data  hydrologic inversion  mathematical-methods  multiquadric method  release  history  optimization   一种基于单幅图像的三维人脸建模与表情合成方法 学位论文  OAI收割 工学硕士, 中国科学院自动化研究所: 中国科学院大学, 2013 舒之昕 收藏  |  浏览/下载：54/0  |  提交时间：2015/09/02 人脸建模  表情合成  主动形状模型  散点插值  运动模型  面部划分  Face Modeling  Expression Synthesis  ASM  Scattered Data Interpolation  Motion Model  Facial Region Segmentation   A MLP-PNN neural network for CCD image super-resolution in wavelet packet domain (EI CONFERENCE) 会议论文  OAI收割 2008 International Conference on Wireless Communications, Networking and Mobile Computing, WiCOM 2008, October 12, 2008 - October 14, 2008, Dalian, China Zhao X.; Fu D.; Zhai L. 收藏  |  浏览/下载：68/0  |  提交时间：2013/03/25 Image super-resolution methods process an input image sequence of a scene to obtain a still image with increased resolution. Classical approaches to this problem involve complex iterative minimization procedures  typically with high computational costs. In this paper is proposed a novel algorithm for super-resolution that enables a substantial decrease in computer load. First  decompose and reconstruct the image by wavelet packet. Before constructing the image  use neural network in place of other rebuilding method to reconstruct the coefficients in the wavelet packet domain. Second  probabilistic neural network architecture is used to perform a scattered-point interpolation of the image sequence data in the wavelet packet domain. The network kernel function is optimally determined for this problem by a MLP-PNN (Multi Layer Perceptron - Probabilistic Neural Network) trained on synthetic data. Network parameters dependent on the sequence noise level. This super-sampled image is spatially Altered to correct finite pixel size effects  to yield the final high-resolution estimate. This method can decrease the calculation cost and get perfect PSNR. Results are presented  showing the quality of the proposed method. 2008 IEEE.