机构

• 水土保持研究所 [2]
• 长春光学精密机械与物... [1]
• 过程工程研究所 [1]

采集方式

• OAI收割 [4]

内容类型

• 期刊论文 [3]
• 会议论文 [1]

发表日期

• 2018 [1]
• 2015 [1]
• 2011 [1]
• 2008 [1]

学科主题

• Agricultur... [2]

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 Spatial Patterns of Relationship Between Wheat Yield and Yield Components in China 期刊论文  OAI收割 INTERNATIONAL JOURNAL OF PLANT PRODUCTION, 2018, 卷号: 12, 期号: 1, 页码: 61-71 作者:  Yu, Q (reprint author), Univ Technol, Sch Life Sci, POB 123, Sydney, NSW 2007, Australia.;  Xiaoya Yang;  Gregory S. McMaster;  Qiang Yu;  Yu, Q (reprint author), Northwest A&F Univ, State Key Lab Soil Eros & Dryland Farming Loess P, Yangling 712100, Peoples R China.   |  收藏  |  浏览/下载：20/0  |  提交时间：2018/09/25 Wheat Yield  Yield Components  Spike Number  Kernel Number  Kernel Weight  Climate Elements   Photosynthetic rates and kernel-filling processes of big-spike wheat (Triticum aestivum L.) during the growth period 期刊论文  OAI收割 NEW ZEALAND JOURNAL OF CROP AND HORTICULTURAL SCIENCE, 2015, 卷号: 43, 期号: 3, 页码: 182-192 作者:  Wang, L.;  Shangguan, Z. 收藏  |  浏览/下载：22/0  |  提交时间：2016/01/19 big-spike wheat  kernel-filling process  kernel yield  photosynthetic rate  Triticum aestivum L  wheat   Genetic loci mapping associated with maize kernel number per ear based on a recombinant inbred line population grown under different nitrogen regimes 期刊论文  OAI收割 Genetics and Molecular Research, 2011, 卷号: 10, 期号: 4, 页码: 3267-3274 作者:  Liu, X. H.;  He, S. L.;  Zheng, Z. P.;  Tan, Z. B.;  Li, Z. 收藏  |  浏览/下载：27/0  |  提交时间：2014/09/30 Maize (Zea mays)  Kernel number per ear  Nitrogen  Quantitative trait  QUANTITATIVE TRAIT LOCI  YIELD COMPONENTS  TROPICAL MAIZE  DROUGHT  TOLERANCE  USE EFFICIENCY  GRAIN-YIELD  QTLS  IDENTIFICATION  L.  RESISTANCE   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.