中国科学院机构知识库网格系统: 检索

Phylotranscriptomic analyses reveal deep gene tree discordance in Camellia (Theaceae) 期刊论文 OAI收割
MOLECULAR PHYLOGENETICS AND EVOLUTION, 2023, 卷号: 188, 页码: 107912
作者: Zhang,Qiong; Folk,Ryan A.; Mo,Zhi-Qiong; Ye,Hang; Zhang,Zhao-Yuan

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收藏 | 浏览/下载：13/0 | 提交时间：2024/07/25

Camellia Gene tree discordance Transcriptome Rapid diversification Selective pressure RNA-SEQ DATA PHYLOGENETIC ANALYSIS NUCLEAR GENES SEQUENCE EVOLUTION RESOLUTION HISTORY INFERENCE ALGORITHM SELECTION

Exploring the Impacts of Data Source, Model Types and Spatial Scales on the Soil Organic Carbon Prediction: A Case Study in the Red Soil Hilly Region of Southern China 期刊论文 OAI收割
REMOTE SENSING, 2022, 卷号: 14, 期号: 20, 页码: 21
作者: Tan, Qiuyuan; Geng, Jing; Fang, Huajun; Li, Yuna; Guo, Yifan

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收藏 | 浏览/下载：42/0 | 提交时间：2022/11/18

soil organic carbon digital soil mapping Sentinel covariates selection model comparison resolution

Feature Rescaling and Fusion for Tiny Object Detection 期刊论文 OAI收割
IEEE ACCESS, 2021, 卷号: 9, 页码: 62946-62955
作者: Liu, Jingwei; Gu, Yi; Han, Shumin; Zhang, Zhibin; Guo, Jiafeng

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收藏 | 浏览/下载：63/0 | 提交时间：2021/12/01

Feature extraction Object detection Semantics Task analysis Training Spatial resolution Shape Tiny object detection nonparametric adaptive selection feature fusion feature pyramid network ensemble model

A Selection Criterion for the Optimal Resolution of Ground-Based Remote Sensing Cloud Images for Cloud Classification 期刊论文 OAI收割
IEEE Transactions on Geoscience and Remote Sensing, 2019, 期号: 3, 页码: 1358-1367
作者: Wang Y(王钰); Wang CH(王春恒); Shi CZ(史存召); Xiao BH(肖柏华)

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收藏 | 浏览/下载：47/0 | 提交时间：2019/05/06

Cloud Image Classification Local Binary Patterns Resolution Selection Kullback– Leibler (Kl) Divergence

An heuristic uncertainty directed field sampling design for digital soil mapping SCI/SSCI论文 OAI收割
2016
作者: Zhang S. J.; Zhu, A. X.; Liu, J.; Yang, L.; Qin, C. Z.

收藏 | 浏览/下载：45/0 | 提交时间：2016/12/16

Legacy samples Individual representativeness Prediction uncertainty Stepwise sampling scheme feedback dynamic patterns fuzzy-logic maps optimization information resolution selection science forests china

Estimating High-Resolution Urban Surface Temperature Using a Hyperspectral Thermal Mixing (HTM) Approach SCI/SSCI论文 OAI收割
2016
作者: Liu K.; Su, H. B.; Li, X. K.

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收藏 | 浏览/下载：26/0 | 提交时间：2017/11/09

High-resolution land surface temperature (LST) hyperspectral remote sensing multiple endmember spectral mixture analysis (SMA) (MESMA) urban application spectral mixture analysis sensible heat-flux impervious surface endmember selection analysis mesma imagery aster area disaggregation separation

Estimating High-Resolution Urban Surface Temperature Using a Hyperspectral Thermal Mixing (HTM) Approach SCI/SSCI论文 OAI收割
2016
作者: Liu K.; Su, H. B.; Li, X. K.; Wang, X.

收藏 | 浏览/下载：31/0 | 提交时间：2016/12/16

High-resolution land surface temperature (LST) hyperspectral remote sensing multiple endmember spectral mixture analysis (SMA) (MESMA) urban application spectral mixture analysis sensible heat-flux impervious surface endmember selection analysis mesma imagery aster area disaggregation separation

Multi-focus image fusion algorithm based on adaptive PCNN and wavelet transform (EI CONFERENCE) 会议论文 OAI收割
International Symposium on Photoelectronic Detection and Imaging 2011: Advances in Imaging Detectors and Applications, May 24, 2011 - May 26, 2011, Beijing, China
Wu Z.-G.; Wang M.-J.; Han G.-L.

收藏 | 浏览/下载：72/0 | 提交时间：2013/03/25

Being an efficient method of information fusion image fusion has been used in many fields such as machine vision medical diagnosis military applications and remote sensing.In this paper Pulse Coupled Neural Network (PCNN) is introduced in this research field for its interesting properties in image processing including segmentation target recognition et al. and a novel algorithm based on PCNN and Wavelet Transform for Multi-focus image fusion is proposed. First the two original images are decomposed by wavelet transform. Then based on the PCNN a fusion rule in the Wavelet domain is given. This algorithm uses the wavelet coefficient in each frequency domain as the linking strength so that its value can be chosen adaptively. Wavelet coefficients map to the range of image gray-scale. The output threshold function attenuates to minimum gray over time. Then all pixels of image get the ignition. So the output of PCNN in each iteration time is ignition wavelet coefficients of threshold strength in different time. At this moment the sequences of ignition of wavelet coefficients represent ignition timing of each neuron. The ignition timing of PCNN in each neuron is mapped to corresponding image gray-scale range which is a picture of ignition timing mapping. Then it can judge the targets in the neuron are obvious features or not obvious. The fusion coefficients are decided by the compare-selection operator with the firing time gradient maps and the fusion image is reconstructed by wavelet inverse transform. Furthermore by this algorithm the threshold adjusting constant is estimated by appointed iteration number. Furthermore In order to sufficient reflect order of the firing time the threshold adjusting constant is estimated by appointed iteration number. So after the iteration achieved each of the wavelet coefficient is activated. In order to verify the effectiveness of proposed rules the experiments upon Multi-focus image are done. Moreover comparative results of evaluating fusion quality are listed. The experimental results show that the method can effectively enhance the edge details and improve the spatial resolution of the image. 2011 SPIE.

Astronomical image restoration through atmosphere turbulence by lucky imaging (EI CONFERENCE) 会议论文 OAI收割
3rd International Conference on Digital Image Processing, ICDIP 2011, April 15, 2011 - April 17, 2011, Chengdu, China
作者: Zhao J.; Wang J.; Zhang S.

收藏 | 浏览/下载：27/0 | 提交时间：2013/03/25

In this paper we develop a lucky imaging system to restore astronomical images through atmosphere turbulence. Our system takes very short exposures on the order of the atmospheric coherence time. The rapidly changing turbulence leads to a very variable point spread function (PSF) and the variability of the PSF leads to some frames having better quality than the rest. Only the best frames are selected aligned and co-added to give a final image with much improved angular resolution. Our system mainly consists of five parts: preprocessing frame selection image registration image reconstruction and image enhancement. Our lucky imaging system has been successfully applied to restore the astronomical images taken by a 1.23m telescope. We have got clear images of moon surface and Jupiter and our system can be demonstrated to greatly improve the imaging resolution through atmospheric turbulence. 2011 Copyright Society of Photo-Optical Instrumentation Engineers (SPIE).

Wavelet analysis of change-points in a non-parametric regression with heteroscedastic variance 期刊论文 OAI收割
JOURNAL OF ECONOMETRICS, 2010, 卷号: 159, 期号: 1, 页码: 183-201
作者: Zhou, Yong; Wan, Alan T. K.; Xie, Shangyu; Wang, Xiaojing

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收藏 | 浏览/下载：86/0 | 提交时间：2018/07/30

lambda-sharp cusp Asymptotic Distribution Convergence Discretized estimator Integral estimator Jump Leave-one-out cross validation Lipschitz continuous Normal distribution Resolution level selection