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Non-rigid 3D models retrieval based on hierarchical matching

Computer Aided Drafting,Design and Manufacturing 2017年第1期27卷 39-47页

作者： Liu Yujie Li Wei Song Yang Gong Weiqing Li Zongmin Li Hua Department of Computer & Communication Engineering China University of Petroleum ChinaPetro (Karamay) Data Center Sinopec Exploration & Production Research Institute (PEPRIS) Key Lab of Intelligent Information Processing Institute of Computing TechnologyChinese Academy of Sciences

In 3D models retrieval, feature description and retrieval of non-rigid model face more complex problems due to the isometry transformation of itself. We introduce the hierarchical combination matching into the feature comparison, and build a map between the divided regions of two models, and then achieve accurate feature matching based on patch-by-patch, which successfully introduces the spatial information into feature matching. Verified by experiment, the 3D model retrieval method proposed in this paper based on hierarchical combination matching can make sure more accurate feature matching, so as to enhance the precision of retrieval.

关键词： non-rigid 3D model shape descriptor spatial distribution hierarchical combination matching

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PROTEOMIC IDENTIFICATION OF INTACT GLYCOPEPTIDES

PROTEOMIC IDENTIFICATION OF INTACT GLYCOPEPTIDES

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第十七届北京分析测试学术报告会暨展览会(BCEIA2017)——分论坛G

作者： Ming-Qi LIU Wen-Feng ZENG Wei-qian CAO Pan FANG Yang ZHANG Jian-Qiang WU Rui-Xiang SUN Si-Min He Peng-Yuan YANG Institutes of Biomedical Sciences and Department Chemistry Fudan University Key Lab of Intelligent Information Processing of Chinese Academy of Sciences(CAS) Institute of Computing TechnologyCASand University of Chinese Academy of Sciences

We have developed a workflow that robustly identifies intact glycopeptides at a proteome scale using stepped-energy mass-spectrometry.A computational strategy called as p Glyco++has been decoded for this workflow,and ... 详细信息

关键词： PROTEOMIC IDENTIFICATION OF INTACT GLYCOPEPTIDES

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An attribute reduction framework for inconsistent decision tables from view of the boundary region

An attribute reduction framework for inconsistent decision t...

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2016 International Conference on Machine Learning and Cybernetics, ICMLC 2016

作者： Qian, Jin Chang, Yu-Hui Lv, Ping Key Laboratory of Cloud Computing and Intelligent Information Processing of Changzhou City Jiangsu University of Technology Changzhou213015 China Jiangsu Key Laboratory of Big Data Analysis Technology/B-DAT Nanjing University of Information Science and Technology Nanjing China

ISBN: (纸本)9781509003891

Attribute reduction is one of the key issues for data preprocess in data mining. Many heuristic attribute reduction algorithms based on discernibility matrix have been proposed for inconsistent decision tables. However, these methods are usually computationally time-consuming. To address this issue, the derived consistent decision tables are defined for different definitions of relative reducts. The computations for different reducts of the original inconsistent decision tables are converted into the computations for their corresponding reducts of the derived consistent datasets. The relative discernibility object pair and the more optimal relative discernibility degree from view of the boundary region are designed to accelerate the attribute reduction process. An efficient attribute reduction framework using relative discernibility degree is proposed for large datasets. Experimental results show that our attribute reduction algorithms are effective and feasible for large inconsistent datasets. © 2016 IEEE.

关键词： Decision tables

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Reflection invariant and symmetry detection

arXiv

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arXiv 2017年

作者： Li, Erbo Li, Hua EON Reality Inc IrvineCA92618 United States Key lab of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China

Symmetry detection and discrimination are of fundamental meaning in science, technology, and engineering. This paper introduces reflection invariants and defines the directional moments(DMs) to detect symmetry for shape analysis and object recognition. And it demonstrates that detection of reflection symmetry can be done in a simple way by solving a trigonometric system derived from the DMs, and discrimination of reflection symmetry can be achieved by application of the reflection invariants in 2D and 3D. Rotation symmetry can also be determined based on that. Also, if none of reflection invariants is equal to zero, then there is no symmetry. And the experiments in 2D and 3D show that all the reflection lines or planes can be deterministically found using DMs up to order six. This result can be used to simplify the efforts of symmetry detection in research areas,such as protein structure, model retrieval, reverse engineering, and machine vision etc. Copyright © 2017, The Authors. All rights reserved.

关键词： Object recognition

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Isomorphism between differential and moment invariants under affine transform

arXiv

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arXiv 2017年

The invariant is one of central topics in science, technology and engineering. The differential invariant is essential in understanding or describing some important phenomena or procedures in mathematics, physics, chemistry, biology or computer science etc. The derivation of differential invariants is usually difficult or complicated. This paper reports a discovery that under the affine transform, differential invariants have similar structures with moment invariants up to a scalar function of transform parameters. If moment invariants are known, relative differential invariants can be obtained by the substitution of moments by derivatives with the same order. Whereas moment invariants can be calculated by multiple integrals, this method provides a simple way to derive differential invariants without the need to resolve any equation system. Since the definition of moments on different manifolds or in different dimension of spaces is well established, differential invariants on or in them will also be well defined. Considering that moments have a strong background in mathematics and physics, this technique offers a new view angle to the inner structure of invariants. Projective differential invariants can also be found in this way with a screening process. Copyright © 2017, The Authors. All rights reserved.

关键词： Affine transforms

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A Forward-Secure Multi-Receiver Signcryption Scheme

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Journal of Harbin Institute of Technology(New Series) 2016年第5期23卷 53-61页

作者： Zhimin Yu Zhengjun Jing Hua Yang Chunsheng Gu Key Laboratory of Cloud Computing and Intelligent Information Processing of Changzhou City Jiangsu University of Technology Changzhou Jiangsu 213001 China College of Computer Nanjing University of Posts and Telecommunications Nanjing 210003 China State Key Laboratory of Information Security Institute of Information Engineering Chinese Academy of Sciences Beijing 100093 China

In order to protect historical ciphertext when the private key leaked in the broadcasting system,the forward-secure multi-receiver signcryption scheme is designed based on the generic graded multilinear mapping encoding structure,which effectively prevents illegal access from intruder to the ciphertext in the past time period when the private key in current time period is *** the generalization of the existing multilinear mapping encoding system,it proposes the generic graded multilinear mapping encoding structure and the generic graded decision Diffie-Hellman *** of the generic graded multilinear mapping encoding system adopted,almost all candidate multilinear mapping encoding systems can automatically adapt to our *** the assumption of generic graded decision Diffie-Hellman problem,it has proved that the scheme has the information confidentiality and unforgeability in the current time *** putting forward the security model of forward-secure multi-receiver signcryption scheme,and under the assumption of generic graded decision Diffie-Hellman problem,it has proved that the scheme has the message forward-confidentiality and *** with other forward-secure public key encryption schemes,the relationship between our scheme and time periods is sub-linear,so it is less complex.

关键词： multilinear mapping forward-secure multi-receiver signcryption confidentiality unforgeability

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Abstractive news summarization based on event semantic link network 26

Abstractive news summarization based on event semantic link ...

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26th International Conference on Computational Linguistics, COLING 2016

作者： Li, Wei He, Lei Zhuge, Hai Key Lab. of Intelligent Information Processing Institute of Computing Technology University of Chinese Academy of Sciences Beijing China Aston University Birmingham United Kingdom

ISBN: (纸本)9784879747020

This paper studies the abstractive multi-document summarization for event-oriented news texts through event information extraction and abstract representation. Fine-grained event mentions and semantic relations between them are extracted to build a unified and connected event semantic link network, an abstract representation of source texts. A network reduction algorithm is proposed to summarize the most salient and coherent event information. New sentences with good linguistic quality are automatically generated and selected through sentences over-generation and greedy-selection processes. Experimental results on DUC 2006 and DUC 2007 datasets show that our system significantly outperforms the state-of-the-art extractive and abstractive baselines under both pyramid and ROUGE evaluation metrics. © 1963-2018 ACL.

关键词： Semantics

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Live cell single molecule-guided Bayesian localization super resolution microscopy

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细胞研究（英文版） 2017年第5期27卷 713-716页

作者： Mingshu Zhang Wenting He Zhiyong Liu Fa Zhang Jennifer Lippincott-Schwartz Key Laboratory of RNA Biology Institute of Biophysics Chinese Academy of Sciences Beijing 100101 China Beijing Key Laboratory of Noncoding RNA Institute of Biophysics Chinese Academy of Sciences Beijing 100101 China Key Lab of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China Janelia Research Campus Howard Hughes Medical Institute Ashburn Virginia 20147 USA

Dear Editor,Many current super resolution (SR) microscopic techniques [1-6] have been successfully applied to image cellular dynamics in living cells,but their applications have remained technically *** cell stimulated emission depletion (STED)/reversible saturable optical linear fluorescence transitions (RESOLFT) microscopy and structured illumination microscopy (SIM)/nonlinear SIM require sophisticated expensive optical setups and specialized expertise for accurate optical *** cell photo-activated localization microscopy (PALM)/stochastic optical reconstruction microscopy (STORM)use less complicated setup;however,a scientific complementary metal-oxide-semiconductor (sCMOS) camera,whose pixel-dependent noise must be characterized and calibrated before use [7],is required for extremely high acquisition speed over tens of thousands of ***,wide field-based SR microscopies have been developed to improve temporal resolution using much fewer time-lapse images (hundreds to thousands) than PALM/STORM [8,9].One of them,Bayesian analysis of the blinking and bleaching (3B) [8],offers enormous potential to resolve ultrastructure and fast cellular dynamics in living cells beyond the diffraction *** its potential,3B analysis is impractical when imaging the nanoscale dynamics in large fields of view over long time periods,as the calculation is extremely time-consuming [8] and/or the analysis consumes large amounts of web resources [10].Another major problem of 3B imaging is the artificial thinning and thickening of structures both in simulated image data and in experimental data [8,10].

关键词： @@

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BigNeuron: a resource to benchmark and predict performance of algorithms for automated tracing of neurons in light microscopy datasets

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Nature methods 2023年第6期20卷 824-835页

作者： Linus Manubens-Gil Zhi Zhou Hanbo Chen Arvind Ramanathan Xiaoxiao Liu Yufeng Liu Alessandro Bria Todd Gillette Zongcai Ruan Jian Yang Miroslav Radojević Ting Zhao Li Cheng Lei Qu Siqi Liu Kristofer E Bouchard Lin Gu Weidong Cai Shuiwang Ji Badrinath Roysam Ching-Wei Wang Hongchuan Yu Amos Sironi Daniel Maxim Iascone Jie Zhou Erhan Bas Eduardo Conde-Sousa Paulo Aguiar Xiang Li Yujie Li Sumit Nanda Yuan Wang Leila Muresan Pascal Fua Bing Ye Hai-Yan He Jochen F Staiger Manuel Peter Daniel N Cox Michel Simonneau Marcel Oberlaender Gregory Jefferis Kei Ito Paloma Gonzalez-Bellido Jinhyun Kim Edwin Rubel Hollis T Cline Hongkui Zeng Aljoscha Nern Ann-Shyn Chiang Jianhua Yao Jane Roskams Rick Livesey Janine Stevens Tianming Liu Chinh Dang Yike Guo Ning Zhong Georgia Tourassi Sean Hill Michael Hawrylycz Christof Koch Erik Meijering Giorgio A Ascoli Hanchuan Peng Institute for Brain and Intelligence Southeast University Nanjing China. Microsoft Corporation Redmond WA USA. Tencent AI Lab Bellevue WA USA. Computing Environment and Life Sciences Directorate Argonne National Laboratory Lemont IL USA. Kaya Medical Seattle WA USA. University of Cassino and Southern Lazio Cassino Italy. Center for Neural Informatics Structures and Plasticity Krasnow Institute for Advanced Study George Mason University Fairfax VA USA. Faculty of Information Technology Beijing University of Technology Beijing China. Beijing International Collaboration Base on Brain Informatics and Wisdom Services Beijing China. Nuctech Netherlands Rotterdam the Netherlands. Janelia Research Campus Howard Hughes Medical Institute Ashburn VA USA. Department of Electrical and Computer Engineering University of Alberta Edmonton Alberta Canada. Ministry of Education Key Laboratory of Intelligent Computation and Signal Processing Anhui University Hefei China. Paige AI New York NY USA. Scientific Data Division and Biological Systems and Engineering Division Lawrence Berkeley National Lab Berkeley CA USA. Helen Wills Neuroscience Institute and Redwood Center for Theoretical Neuroscience UC Berkeley Berkeley CA USA. RIKEN AIP Tokyo Japan. Research Center for Advanced Science and Technology (RCAST) The University of Tokyo Tokyo Japan. School of Computer Science University of Sydney Sydney New South Wales Australia. Texas A&M University College Station TX USA. Cullen College of Engineering University of Houston Houston TX USA. Graduate Institute of Biomedical Engineering National Taiwan University of Science and Technology Taipei Taiwan. National Centre for Computer Animation Bournemouth University Poole UK. PROPHESEE Paris France. Department of Neuroscience Columbia University New York NY USA. Mortimer B. Zuckerman Mind Brain Behavior Institute Columbia University New York NY USA. Department of Computer Science Northern Illinois Universit

BigNeuron is an open community bench-testing platform with the goal of setting open standards for accurate and fast automatic neuron tracing. We gathered a diverse set of image volumes across several species that is representative of the data obtained in many neuroscience laboratories interested in neuron tracing. Here, we report generated gold standard manual annotations for a subset of the available imaging datasets and quantified tracing quality for 35 automatic tracing algorithms. The goal of generating such a hand-curated diverse dataset is to advance the development of tracing algorithms and enable generalizable benchmarking. Together with image quality features, we pooled the data in an interactive web application that enables users and developers to perform principal component analysis, t-distributed stochastic neighbor embedding, correlation and clustering, visualization of imaging and tracing data, and benchmarking of automatic tracing algorithms in user-defined data subsets. The image quality metrics explain most of the variance in the data, followed by neuromorphological features related to neuron size. We observed that diverse algorithms can provide complementary information to obtain accurate results and developed a method to iteratively combine methods and generate consensus reconstructions. The consensus trees obtained provide estimates of the neuron structure ground truth that typically outperform single algorithms in noisy datasets. However, specific algorithms may outperform the consensus tree strategy in specific imaging conditions. Finally, to aid users in predicting the most accurate automatic tracing results without manual annotations for comparison, we used support vector machine regression to predict reconstruction quality given an image volume and a set of automatic tracings.

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Memory-enhanced Decoder for neural machine translation

Memory-enhanced Decoder for neural machine translation

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2016 Conference on Empirical Methods in Natural Language processing, EMNLP 2016

作者： Wang, Mingxuan Lu, Zhengdong Li, Hang Liu, Qun Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences China Noah's Ark Lab Huawei Technologies ADAPT Centre School of Computing Dublin City University Ireland

ISBN: (纸本)9781945626258

We propose to enhance the RNN decoder in a neural machine translator (NMT) with external memory, as a natural but powerful extension to the state in the decoding RNN. This memory-enhanced RNN decoder is called MEMDEC. At each time during decoding, MEMDEC will read from this memory and write to this memory once, both with content-based addressing. Unlike the unbounded memory in previous work(Bahdanau et al., 2014) to store the representation of source sentence, the memory in MEMDEC is a matrix with predetermined size designed to better capture the information important for the decoding process at each time step. Our empirical study on Chinese-English translation shows that it can improve by 4.8 BLEU upon Groundhog and 5.3 BLEU upon on Moses, yielding the best performance achieved with the same training set. © 2016 Association for Computational Linguistics

关键词： Neural machine translation

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