中国科学院机构知识库网格系统: 检索

Delimiting 33 Carpinus (Betulaceae) species with a further phylogenetic inference 期刊论文 OAI收割
AOB PLANTS, 2022, 期号: _, 页码: -
作者: Dong, Congcong; Lu, Zhiqiang; Zhang, Han; Liu, Jianquan; Li, Minjie

|

收藏 | 浏览/下载：44/0 | 提交时间：2022/04/25

Carpinus ITS sequences species delimitation phylogeny

A phylogenetic census of global diversity of gut anaerobic fungi and a new taxonomic framework 期刊论文 OAI收割
FUNGAL DIVERSITY, 2018, 卷号: 89, 期号: 1, 页码: 253-266
作者: Paul, Shyam Sundar; Bu, Dengpan; Xu, Jianchu; Hyde, Kevin D.; Yu, Zhongtang

|

收藏 | 浏览/下载：23/0 | 提交时间：2018/04/28

Anaerobic Fungi Global Diversity Its1 Sequences Rumen Taxonomic Framework

A new species of Saxifraga in section Ciliatae subsection Gemmiparae (Saxifragaceae) from Sichuan province, China 期刊论文 OAI收割
PHYTOTAXA, 2018, 卷号: 333, 期号: 2, 页码: 228-234
作者: Chen, Shilong; Gornall, Richard J.; Gao, Qingbo; Zhang, Zhuoxin

|

收藏 | 浏览/下载：28/0 | 提交时间：2018/07/25

Saxifraga Section Ciliatae subSection Gemmiparae Floral Morphology Trnl-f Its Dna Sequences

Redescription of Clitocybe umbrinopurpurascens (Basidiomycota, Agaricales) and revision of Neohygrophorus and Pseudoomphalina 期刊论文 OAI收割
PHYTOTAXA, 2015, 卷号: 219, 期号: 1, 页码: 43-57
作者: Lavorato, Carmine; Vizzini, Alfredo; Ge, Zai-Wei; Contu, Marco

收藏 | 浏览/下载：28/0 | 提交时间：2016/01/19

Agaricomycetes tricholomatoid clade amyloid spores ITS and nucLSU sequences taxonomy

Paxillus orientalis sp nov (Paxillaceae, Boletales) from south-western China based on morphological and molecular data and proposal of the new subgenus Alnopaxillus 期刊论文 OAI收割
MYCOLOGICAL PROGRESS, 2014, 卷号: 13, 期号: 2, 页码: 333-342
作者: Gelardi, Matteo

收藏 | 浏览/下载：25/0 | 提交时间：2014/06/23

Basidiomycota Boletineae Chinese ectomycorrhizal fungi ITS sequences Molecular phylogeny Taxonomy

Lepiota coloratipes, a new species for Lepiota rufipes ss. Auct. europ. non ss. orig. 期刊论文 OAI收割
MYCOLOGICAL PROGRESS, 2014, 卷号: 13, 期号: 1, 页码: 171-179
作者: Vizzini, Alfredo; Liang, Jun F.; Jancovicova, Sona

收藏 | 浏览/下载：45/0 | 提交时间：2014/04/09

Basidiomycota Agaricales Agaricaceae Hymeniform pileus covering ITS sequences Taxonomy

Seasonal variation of dominant free-floating and attached Ulva species in Rudong coastal area, China 期刊论文 OAI收割
HARMFUL ALGAE, 2013, 卷号: 28, 页码: 46-54
作者: Han, Wei; Chen, Li-Ping; Zhang, Jian-Heng; Tian, Xiao-Ling; Hua, Liang

|

收藏 | 浏览/下载：7/0 | 提交时间：2023/04/25

Attached population Free-floating population Green tides ITS sequences Molecular identification Porphyra aquaculture raft Ulva prolifera 5S rDNA spacer regions

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：73/0 | 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.

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.

Contour extracting with combination particle filtering and em algorithm (EI CONFERENCE) 会议论文 OAI收割
International Symposium on Photoelectronic Detection and Imaging, ISPDI 2007: Related Technologies and Applications, September 9, 2007 - September 12, 2007, Beijing, China
Meng B.; Zhu M.

收藏 | 浏览/下载：26/0 | 提交时间：2013/03/25

The problem of extracting continuous structures from images is a difficult issue in early pattern recognition and image processings[1]. Tracking with contours in a filtering framework requires a dynamical model for prediction. Recently Particle filter is widely used because its multiple hypotheses and versatility within framework. However the good choice of the propagation function is still its main problem. In this paper an improved particle filter EM-PF algorithm is proposed which using the EM (Expectation-Maximization) algorithm to learn the dynamical models. The EM algorithm can explicitly learn the parameters of the dynamical models from training sequences. The advantage of using the EM algorithm in particle filter is that it is capable of improve tracking contour by having accurate model parameters. Though the experiment results we show how our EM-PF can be applied to produces more robust and accurate extracting.