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检索条件"任意字段=6th International Conference on Bioinformatics Models, Methods and Algorithms, BIOINFORMATICS 2015"

共 237 条记录，以下是181-190 订阅

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6th international Euro-Mediterranean conference on Digital Heritage, EuroMed 2016

6th International Euro-Mediterranean Conference on Digital H...

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6th international Euro-Mediterranean conference on Digital Heritage, EuroMed 2016

ISBN: (纸本)9783319484952

the proceedings contain 73 papers. the special focus in this conference is on 3D Reconstruction, 3D Modelling, Heritage Building Information models, Innovative methods on Risk Assesment, Monitoring, Intangible Cultural Heritage Documentation, Non-destructive Techniques in Cultural Heritage Conservation, Digital Cultural Heritage in Education, Learning and Training. the topics include: Implementation and usage scenarios of a participatory platform for cultural environments;proportional systems in the design of the cathedral of St. George of the Greeks, Cyprus;multi-scale 3D modelling of damaged cultural sites;low cost technique for accurate geometric documentation of complex monuments by non-experts;implementation analysis and design for energy efficient intervention on heritage buildings;historic BIM in the cloud;parameterizing the geometry and visualizing the lighting method of byzantine church domes;a study of 3D digital simulation analysis of fire charring degree of wood construction of Chinese traditional architecture;diagnostic activities for the planned and preventive conservation of mosaic pavements;researching knowledge concerns in virtual historical architecture;surveying illusory architectures painted on vaulted surfaces;internal 3D printing of intricate structures;digital preservation of cultural heritage;debate and considerations on using videos for cultural heritage from social media for 3D modelling;investigations of low-cost systems for 3D reconstruction of small objects;from SfM to semantic-aware BIM objects of architectural elements;an interdisciplinary study on the ancient Egyptian wines;towards the design of a user-friendly and trustworthy mobile system for museums and contextualizing 3D cultural heritage.

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Approximate matching between a context-free grammar and a finite-state automaton

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18th international conference on Implementation and Application of Automata, CIAA 2013

作者： Han, Yo-Sub Ko, Sang-Ki Salomaa, Kai Department of Computer Science Yonsei University 50 Yonsei-Ro Seodaemun-Gu Seoul 120-749 Korea Republic of School of Computing Queen's University Kingston ON K7L 3N6 Canada

ISBN: (纸本)9783642392733

Given a context-free grammar (CFG) and a finite-state automaton (FA), we tackle the problem of computing the most similar pair of strings from two languages. We in particular consider three different gap cost models, linear, affine and concave models, that are crucial for finding a proper alignment between two bio sequences. We design efficient algorithms for computing the edit-distance between a CFG and an FA under these gap cost models. the time complexity of our algorithm for computing the linear or affine gap distance is polynomial and the time complexity for the concave gap distance is exponential. © 2013 Springer-Verlag.

关键词： Context free grammars

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Efficient pseudo-relevance feedback methods for collaborative filtering recommendation 38th

Efficient pseudo-relevance feedback methods for collaborativ...

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38th European conference on Information Retrieval Research, ECIR 2016

作者： Valcarce, Daniel Parapar, Javier Barreiro, Álvaro Information Retrieval Lab Computer Science Department University of A Coruña A Coruña Spain

ISBN: (纸本)9783319306704

Recently, Relevance-Based Language models have been demonstrated as an effective Collaborative Filtering approach. Nevertheless, this family of Pseudo-Relevance Feedback techniques is computationally expensive for applying them to web-scale data. Also, they require the use of smoothing methods which need to be tuned. these facts lead us to study other similar techniques with better trade-offs between effectiveness and efficiency. Specifically, in this paper, we analyse the applicability to the recommendation task of four well-known query expansion techniques with multiple probability estimates. Moreover, we analyse the effect of neighbourhood length and devise a new probability estimate that takes into account this property yielding better recommendation rankings. Finally, we find that the proposed algorithms are dramatically faster than those based on Relevance-Based Language models, they do not have any parameter to tune (apart from the ones of the neighbourhood) and they provide a better trade-off between accuracy and diversity/ novelty. © Springer international Publishing Switzerland 2016.

关键词： Collaborative filtering

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Nonlinear graph fusion for multi-modal classification of Alzheimer’s disease 1

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6th international Workshop on Machine Learning in Medical Imaging, MLMI 2015 and Held in Conjunction with 18th international conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2015

作者： Tong, Tong Gray, Katherine Gao, Qinquan Chen, Liang Rueckert, Daniel Department of Computing Imperial College London London United Kingdom Fujian Province Key Lab of MIPT Fuzhou University Fuzhou China

ISBN: (数字)9783319248882

ISBN: (纸本)9783319248875

Recent studies have demonstrated that biomarkers from multiple modalities contain complementary information for the diagnosis of Alzheimer’s disease (AD) and its prodromal stage mild cognitive impairment (MCI). In order to fuse data from multiple modalities, most previous approaches calculate a mixed kernel or a similarity matrix by linearly combining kernels or similarities from multiple modalities. However, the complementary information from multi-modal data are not necessarily linearly related. In addition, this linear combination is also sensitive to the weights assigned to each modality. In this paper, we propose a nonlinear graph fusion method to efficiently exploit the complementarity in the multi-modal data for the classification of AD. Specifically, a graph is first constructed for each modality individually. Afterwards, a single unified graph is obtained via a nonlinear combination of the graphs in an iterative cross diffusion process. Using the unified graphs, we achieved classification accuracies of 91.8% between AD subjects and normal controls (NC), 79.5% between MCI subjects and NC and 60.2% in a three-way classification, which are competitive with state-of-the-art results. © Springer international Publishing Switzerland 2015.

关键词： Iterative methods

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Machine learning on high dimensional shape data from subcortical brain surfaces: A comparison of feature selection and classification methods 1

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作者： Wade, Benjamin S. C. Joshi, Shantanu H. Gutman, Boris A. thompson, Paul M. Imaging Genetics Center USC Marina del ReyCA United States Ahmanson-Lovelace Brain Mapping Center UCLA Los AngelesCA United States

ISBN: (数字)9783319248882

ISBN: (纸本)9783319248875

Recently, high-dimensional shape data (HDSD) has been demonstrated to be informative in describing subcortical brain morphometry in several disorders. While HDSD may serve as a biomarker of disease, its high dimensionality may require careful treatment in its application to machine learning. Here, we compare several possible approaches for feature selection and pattern classification using HDSD. We explore the efficacy of three candidate feature selection (FS) methods: Guided Random Forest (GRF), LASSO and no feature selection (NFS). Each feature set was applied to three classifiers: Random Forest (RF), Support Vector Machines (SVM) and Naïve Bayes (NB). Each model was cross-validated using two diagnostic contrasts: Alzheimer’s Disease and mild cognitive impairment;each relative to matched controls. GRF and NFS outperformed LASSO as FS methods and were comparably competitive. NB underperformed relative to RF and SVM, which were comparable in performance. Our results advocate the NFS-RF approach for its speed, simplicity and interpretability. © Springer international Publishing Switzerland 2015.

关键词： Feature Selection

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Configuration of hydro power plant mathematical models 4th

Configuration of hydro power plant mathematical models

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4th D-A-CH conference on Energy Informatics, EI 2015

作者： Barry, Michael Schillinger, Moritz Weigt, Hannes Schumann, René Smart Infrastructure Laboratory HES-SO Valais/Wallis Rue de Technopôle 3 Sierre3960 Switzerland Forschungsstelle Nachhaltige Energie- und Wasserversorgung University Basel Peter Merian-Weg 6 Basel4002 Switzerland

ISBN: (纸本)9783319258751

the ongoing energy transition towards large shares of renewable generation poses challenges for hydro power producers. We revisit the problem of optimising the operation of hydro power plants using mathematical modelling, but utilising computer science concepts in the design of the models and configuration of these models. We use a modular design allowing us to activate features, such as what markets or which technical aspects to consider, by activating or deactivating a specific module. In this paper we give an example of how our method can be used to configure which markets a model should operate on. Furthermore, we use a configuration process based on the SPEA2 evolutionary algorithm to explore the relationship between the scale of the model and the time required to solve it. Such methods assist in identifying configurations that are the best fit in terms of runtime, realism and accuracy. © Springer international Publishing Switzerland 2015.

关键词： Hydroelectric power

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6D Pose Estimation for Industrial Applications 2nd

6D Pose Estimation for Industrial Applications

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2nd international Workshop on Recent Advances in Digital Security: Biometrics and Forensics, BioFor 2019, 1st international Workshop on Pattern Recognition for Cultural Heritage, PatReCH 2019, 1st international Workshop eHealth in the Big Data and Deep Learning Era, e-BADLE 2019, international Workshop on Deep Understanding Shopper Behaviors and Interactions in Intelligent Retail Environments, DEEPRETAIL 2019 and Industrial session held at the 20th international conference on Image Analysis and Processing, ICIAP 2019

作者： Cunico, Federico Carletti, Marco Cristani, Marco Masci, Fabio Conigliaro, Davide Department of Computer Science University of Verona Verona Italy Genova Italy The Edge Company Srl Rimini Italy Humatics Srl Verona Italy

ISBN: (纸本)9783030307530

Object pose estimation is important for systems and robots to interact with the environment where the main challenge of this task is the complexity of the scene caused by occlusions and clutters. A key challenge is performing pose estimation leveraging on both RGB and depth information: prior works either extract information from the RGB image and depth separately or use costly post-processing steps, limiting their performances in highly cluttered scenes and real-time applications. Traditionally, the pose estimation problem is tackled by matching feature points between 3D models and images. However, these methods require rich textured models. In recent years, the raising of deep learning has offered an increasing number of methods based on neural networks, such as DSAC++, PoseCNN, DenseFusion and SingleShotPose. In this work, we present a comparison between two recent algorithms, DSAC++ and DenseFusion, focusing on computational cost, performance and applicability in the industry. © 2019, Springer Nature Switzerland AG.

关键词： Textures

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Unsupervised learning and mapping of brain fMRI signals based on hidden Semi-Markov event sequence models

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6th international conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2003

作者： Faisan, Sylvain thoraval, Laurent Armspach, Jean-Paul Heitz, Fabrice Laboratoire des Sciences de l’Image de l’Informatique et de la Télédétection LSIIT/MIV - UMR CNRS 7005 ENSPS Bd. Sébastien Brant IllkirchF-67400 France Institut de Physique Biologique 4 Rue Kirschleger Strasbourg CedexF-67085 France

ISBN: (纸本)3540204644

Most methods used in functional MRI (fMRI) brain mapping require restrictive prior knowledge about the shape of the active bloodoxygenation- level-dependent (BOLD) response, thus leading to suboptimal or invalid inference. To solve this problem, we propose to assess local neural activity in terms of time alignment between the sequence of BOLD dynamics changes of interest and an Hidden Semi-Markov Event Sequence Model (HSMESM) of brain activation. the topology of the HSMESM is built from the deterministic transitions of the input stimulation paradigm and its parameters are automatically and iteratively learned from all intracranial fMRI signals. the brain mapping results achieved by HSMESMs in language processing demonstrate the relevance of such models in BOLD fMRI, especially to cope with strong variabilities of the active BOLD signal across time, brain, experiments and subjects. © Springer-Verlag Berlin Heidelberg 2003.

关键词： Brain mapping

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Detection of abrupt changes in spatial relationships in video sequences 4th

Detection of abrupt changes in spatial relationships in vide...

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4th international conference on Pattern Recognition Applications and methods, ICPRAM 2015

作者： Abou-Elailah, Abdalbassir Gouet-Brunet, Valerie Bloch, Isabelle LTCI CNRS Télécom ParisTech Université Paris-Saclay Paris France Université Paris-Est IGN SRIG MATIS 73 avenue de Paris Saint Mandé94160 France

ISBN: (纸本)9783319276762

Detecting unusual events in video sequences is very challenging due to cluttered background, the difficulties of accurate extraction and tracking of moving objects, illumination change, etc. In this work, we focus on detecting strong changes in spatial relationships between moving objects in video sequences, with a limited knowledge of the objects. In this approach, the spatial relationships between two objects of interest are modeled using angle and distance histograms as examples. To evaluate the evolution of the spatial relationships during time, the distances between two angle or distance histograms at two different instants in time are estimated. In addition, a combination approach is proposed to combine the evolution of directional (angle) and metric (distance) relationships. Studying the evolution of the spatial relationships during time allows us to detect the ruptures in such spatial relationships. this study can constitute a promising step toward event detection in video sequences, with few a priori models on the objects. © Springer international Publishing Switzerland 2015.

关键词： Graphic methods

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A new method for inconsistent multicriteria classification

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6th international conference on Rough Sets and Knowledge Technology, RSKT 2011

作者： Deng, Weibin Wang, Guoyin Yang, Shuangxia Hu, Feng School of Information Science and Technology Southwest Jiaotong University Chengdu 610031 China Institute of Computer Science and Technology Chongqing University of Posts and Telecommunications Chongqing 400065 China

ISBN: (纸本)9783642244247

three relaxation models (VC-DRSA, VP-DRSA and ISVP-DRSA) of DRSA have been proposed to relax the strict dominance principle. However, the classification performance of these models is affected by the value of consistency level l. Until now, the value of l is set according to prior domain knowledge. But no one knows which value is the best and the reason. To address the multicriteria classification problem, we propose a new method in this paper. A new uncertainty measure is defined and an algorithm for transforming inconsistent preference-ordered systems into consistent ones (TIPStoC) is designed in this paper. An iterative approach is adopted in TIPStoC algorithm. We find that inconsistent preference-ordered information systems can be transformed into consistent systems with low computation complexity, and without losing useful information. the classification performance will be improved with the decision rules induced from the consistent systems. Besides, the value of consistency level l is set to 1.0 without depending on prior knowledge. Finally, the procedure of TIPStoC algorithm is illustrated by a real example and the efficiency of the new method is proved by experiments. © 2011 Springer-Verlag.

关键词： Iterative methods

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