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检索条件"任意字段=6th IAPR International Conference on Pattern Recognition in Bioinformatics"

共 1869 条记录，以下是371-380 订阅

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Combined and Weighted Features for Robust Multispectral Face recognition 6th

Combined and Weighted Features for Robust Multispectral Face...

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6th IFIP international conference on Computational Intelligence and Its Applications (CIIA)

作者： Benamara, Nadir Kamel Zigh, Ehlem Stambouli, Tarik Boudghene Keche, Mokhtar Univ Sci & Technol Oran Mohamed Boudiaf USTO MB Lab Signals & Images LSI Oran Algeria Natl Inst Telecommun & ICT Oran INTTIC Lab Res Appl ICT LARATIC Oran Algeria

ISBN: (纸本)9783319897431;9783319897424

Face recognition has been very popular in recent years, for its advantages such as acceptance by the wide public and the price of cameras, which became more accessible. the majority of the current facial biometric systems use the visible spectrum, which suffers from some limitations, such as sensitivity to light changing, pose and facial expressions. the infrared spectrum is more relevant to facial biometric, for its advantages such as robustness to illumination change. In this paper, we propose two multispectral face recognition approaches that use both the visible and infrared spectra. We tested the new approaches with Uniform Local Binary pattern (uLBP) as a local descriptor and Zernike Moments as a global descriptor on IRIS thermal/Visible and CSIST Lab 2 databases. the experimental results clearly demonstrate the effectiveness of our multispectral face recognition system compared to a system that uses a single spectrum.

关键词： Multispectral face recognition Infrared Uniform Local Binary pattern Zernike moments Feature fusion

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An Interactive Strategy to Visualize Common Subgraphs in Protein-Ligand Interaction 6th

An Interactive Strategy to Visualize Common Subgraphs in Pro...

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6th international Work-conference on bioinformatics and Biomedical Engineering (IWBBIO)

作者： Fassio, Alexandre V. Santana, Charles A. Cerqueira, Fabio R. da Silveira, Carlos H. Romanelli, Joao P. R. de Melo-Minardi, Raquel C. Silveira, Sabrina de A. Univ Fed Minas Gerais BR-31270901 Belo Horizonte MG Brazil Univ Fed Vicosa BR-36570900 Vicosa MG Brazil Univ Fed Itajuba BR-35903087 Itabira MG Brazil

ISBN: (纸本)9783319787220;9783319787237

Interactions between proteins and ligands play an important role in biological processes of living systems. For this reason, the development of computational methods to facilitate the understanding of the ligand-receptor recognition process is fundamental, since this comprehension is a major step towards ligand prediction, target identification, lead discovery, among others. this article presents a visual interactive interface to explore protein-ligand interactions and their conserved substructures for a set of similar proteins. the protein-ligand interface is modeled as bipartite graphs, where nodes represents protein and ligand atoms, and edges depicts interactions between them. Such graphs are the input to search for frequent subgraphs that are the conserved interaction patterns over the datasets. To illustrate the potential of our strategy, we used two test datasets, Ricin and human CDK2. Availability: http:// ***/similar to alexandrefassio/gremlin/.

关键词： Visualization pattern Protein Ligand Graph Data mining

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Spatial co-location pattern mining 6th

Spatial co-location pattern mining

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6th international conference on Big Data Analytics, BDA 2018

作者： Gunturi, Venkata M. V. IIT-Ropar Rupnagar India

ISBN: (纸本)9783030047795

Given a spatial dataset containing instances of a set of spatial Boolean feature-types, the problem of spatial co-location pattern mining aims to determine a subset of feature-types which are frequently co-located in space. Spatial Co-location patterns have a wide range of applications in the domains such as ecology, public health and public safety. For instance, in an ecological dataset containing event instances corresponding to different bird species and vegetation types, spatial co-location patterns may revel that a particular species of birds prefer a particular kind of trees for their nests. Similarly, in a crime dataset, spatial co-location may revel a pattern that drunk-driving cases are co-located with bar locations. this article presents a gentle introduction to spatial co-location pattern mining. It introduces a well studied interest measure called participation index for co-location mining and, then discusses an algorithm to determine patterns having high participation index in a spatial dataset. © Springer Nature Switzerland AG 2018.

关键词： Birds

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Stock Price Forecasting Over Adaptive Timescale Using Supervised Learning and Receptive Fields 6th

Stock Price Forecasting Over Adaptive Timescale Using Superv...

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6th international conference on Mining Intelligence and Knowledge Exploration (MIKE)

作者： Cimino, Mario G. C. A. Dalla Bona, Federico Foglia, Pierfrancesco Monaco, Manilo Prete, Cosimo A. Vaglini, Gigliola Univ Pisa Dept Informat Engn I-56122 Pisa Italy Trading Methods SL Las Palmas Gran Canaria 35100 Gran Canaria Spain

ISBN: (纸本)9783030059187;9783030059170

pattern recognition in financial time series is not a trivial task, due to level of noise, volatile context, lack of formal definitions and high number of pattern variants. A current research trend involves machine learning techniques and online computing. However, medium-term trading is still based on humancentric heuristics, and the integration with machine learning support remains relatively unexplored. the purpose of this study is to investigate potential and perspectives of a novel architectural topology providing modularity, scalability and personalization capabilities. the proposed architecture is based on the concept of Receptive Fields (RF), i.e., sub-modules focusing on specific patterns, that can be connected to further levels of processing to analyze the price dynamics on different granularities and different abstraction levels. Both Multilayer Perceptrons (MLP) and Support Vector Machines (SVM) have been experimented as a RF. Early experiments have been carried out over the FTSEMIB index.

关键词： Stock price forecasting pattern recognition Artificial neural network Support vector machine

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pattern matching in link streams: A token-based approach 1

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39th international conference on Application and theory of Petri Nets and Concurrency, PETRI NETS 2018

作者： Bertrand, Clément Klaudel, Hanna Latapy, Matthieu Peschanski, Frédéric IBISC Univ Evry Université Paris-Saclay Evry91025 France LIP6 Sorbonne Université Paris France

ISBN: (数字)9783319912684

ISBN: (纸本)9783319912677

Link streams model the dynamics of interactions in complex distributed systems as sequences of links (interactions) occurring at a given time. Detecting patterns in such sequences is crucial for many applications but it raises several challenges. In particular, there is no generic approach for the specification and detection of link stream patterns in a way similar to regular expressions and automata for text patterns. To address this, we propose a novel automata framework integrating both timed constraints and finite memory together with a recognition algorithm. the algorithm uses structures similar to tokens in high-level Petri nets and includes non-determinism and concurrency. We illustrate the use of our framework in real-world cases and evaluate its practical performances. © 2018, Springer international Publishing AG, part of Springer Nature.

关键词： pattern matching

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6th international conference on Analysis of Images, Social Networks and Texts, AIST 2017

6th International Conference on Analysis of Images, Social N...

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6th international conference on Analysis of Images, Social Networks and Texts, AIST 2017

ISBN: (纸本)9783319730127

the proceedings contain 37 papers. the special focus in this conference is on Analysis of Images, Social Networks and Texts. the topics include: Rotations and interpretability of word embeddings: the case of the Russian language;HuGaDB: Human gait database for activity recognition from wearable inertial sensor networks;on finding maximum cardinality subset of vectors with a constraint on normalized squared length of vectors sum;using cluster analysis for characteristics detection in software defect reports;a machine learning approach to enhanced oil recovery prediction;an approach to establishing the correspondence of spatial objects on heterogeneous maps based on methods of computational topology;predicting winning team and probabilistic ratings in “Dota 2” and “Counter-strike: Global offensive” video games;bagging prediction for censored data: Application for theatre demand;Original loop-closure detection algorithm for monocular vSLAM;automated detection of non-relevant posts on the russian imageboard “2ch”: Importance of the choice of word representations;organizing multimedia data in video surveillance systems based on face verification with convolutional neural networks;satellite image forgery detection based on buildings shadows analysis;nonlinear dimensionality reduction of hyperspectral data using spectral correlation as a similarity measure;large-scale shape retrieval with sparse 3D convolutional neural networks;floor-ladder framework for human face beautification;Array DBMS and satellite imagery: Towards big raster data in the cloud;impulsive noise removal from color images with morphological filtering;an exact polynomial algorithm for the outerplanar facility location problem with improved time complexity;approximation algorithms for the maximum m-peripatetic salesman problem;scientific matchmaker: Collaborator recommender system.

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Proceedings - 2018 international conference on 3D Vision, 3DV 2018

Proceedings - 2018 International Conference on 3D Vision, 3D...

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6th international conference on 3D Vision, 3DV 2018

ISBN: (纸本)9781538684252

the proceedings contain 81 papers. the topics discussed include: keep it unreal: bridging the realism gap for 2.5D recognition with geometry priors only;surface light field fusion;joint material and illumination estimation from photo sets in the wild;patch-based non-rigid 3D reconstruction from a single depth stream;sparse and dense data with CNNs: depth completion and semantic segmentation;multi-scale CNN stereo and pattern removal technique for underwater active stereo system;a multi-resolution approach for color correction of textured meshes;multi-scale direct sparse visual odometry for large-scale natural environment;detailed human avatars from monocular video;and DeepHPS: end-to-end estimation of 3D hand pose and shape by learning from synthetic depth.

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6th international conference on Context-Aware Systems and Applications, ICCASA 2017 and 3rd international conference on Nature of Computation and Communication, ICTCC 2017

6th International Conference on Context-Aware Systems and Ap...

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6th international conference on Context-Aware Systems and Applications, ICCASA 2017 and 3rd international conference on Nature of Computation and Communication, ICTCC 2017

ISBN: (纸本)9783319778174

the proceedings contain 22 papers. the special focus in this conference is on . the topics include: the Context-Aware Calculating Method in Language Environment Based on Hedge Algebras Approach to Improve Result of Forecasting Time Series;algebraic Operations in Fuzzy Object-Oriented Databases Based on Hedge Algebras;context-Adaptive Values-Based Games for the Young: Responsible Decision Making for a Sustainable World;applying and Deploying Cyber Physical System in Monitoring and Managing Operations Under Mines and Underground Works;the Method of Maintaining Data Consistency in Allocating Resources for the P2P Network Model;Fragmentation in Distributed Database Design Based on KR Rough Clustering Technique;architectural Framework for Context Awareness and Health Conscious Applications on Mobile Devices;holistic Personas and the Five-Dimensional Framework to Assist Practitioners in Designing Context-Aware Accounting Information System e-Learning Applications;abnormal Behavior Detection Based on Smartphone Sensors;A Context Adaptive Framework for IT Governance, Risk, Compliance and Security;An Effective of Data Organizing Method Combines with Naïve Bayes for Vietnamese Document Retrieval;an Effective Time Varying Delay Estimator Applied to Surface Electromyographic Signals;the Optimal Solution of Communication Resource Allocation in Distributed System Integrated on Cloud Computing;hybrid Classifier by Integrating Sentiment and Technical Indicator Classifiers;visualizing Space-Time Map for Bus;generation of Power State Machine for Android Devices;modeling Self-adaptation - A Possible Endeavour?;enhancement of Wu-Manber Multi-pattern Matching Algorithm for Intrusion Detection System;goal-Capability-Commitment Based Context-Aware Collaborative Adaptive Diagnosis and Compensation;traffic Incident recognition Using Empirical Deep Convolutional Neural Networks Model.

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6th CCF international conference on Natural Language Processing and Chinese Computing, NLPCC 2017

6th CCF International Conference on Natural Language Process...

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6th CCF international conference on Natural Language Processing and Chinese Computing, NLPCC 2017

ISBN: (纸本)9783319736174

the proceedings contain 86 papers. the special focus in this conference is on Natural Language Processing and Chinese Computing. the topics include: A deep learning way for disease name representation and normalization;Externally controllable RNN for implicit discourse relation classification;random projections with bayesian priors;a convolutional attention model for text classification;shortcut sequence tagging;look-ahead attention for generation in neural machine translation;modeling indicative context for statistical machine translation;augmenting neural sentence summarization through extractive summarization;a semantic concept based unknown words processing method in neural machine translation;Research on mongolian speech recognition based on FSMN;using bilingual segments to improve interactive machine translation;Unsupervised automatic text style transfer using LSTM;optimizing topic distributions of descriptions for image description translation;automatic document metadata extraction based on deep networks;a semantic representation enhancement method for Chinese news headline classification;neural domain adaptation with contextualized character embedding for Chinese word segmentation;identification of influential users based on topic-behavior influence tree in social networks;abstractive document summarization via neural model with joint attention;an effective approach for Chinese news headline classification based on multi-representation mixed model with attention and ensemble learning;Cascaded LSTMs based deep reinforcement learning for goal-driven dialogue;domain-specific Chinese word segmentation with document-level optimization;will repeated reading benefit natural language understanding?;a deep convolutional neural model for character-based Chinese word segmentation;chinese zero pronoun resolution: A chain to chain approach;towards better Chinese zero pronoun resolution from discourse perspective;extractive single document summarization via multi-feature

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6th international conference on Frontiers of Intelligent Computing: theory and Applications, FICTA-2017

6th International Conference on Frontiers of Intelligent Com...

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6th international conference on Frontiers of Intelligent Computing: theory and Applications, FICTA-2017

ISBN: (纸本)9789811075650

the proceedings contain 66 papers. the special focus in this conference is on . the topics include: AKM—Augmentation of K-means clustering algorithm for big data;face recognition using local binary pattern-blockwise method;Social group optimization (SGO) for clustering in wireless sensor networks;Implementation of high-performance floating point divider using pipeline architecture on FPGA;GA_DTNB: A hybrid classifier for medical data diagnosis;applications of spiking neural network to predict software reliability;An optimized rendering solution for ranking heterogeneous VM instances;gender prediction in author profiling using relieff feature selection algorithm;optimal coordination of overcurrent relays using simulated annealing and brute force algorithms;a new term weight measure for gender prediction in author profiling;the close-loop antenna array control system for automatic optimization in LTE and 3G network;Tumour classification in graph-cut segmented mammograms using GLCM features-fed SVM;Improving feature selection using elite breeding QPSO on gene data set for cancer classification;Epileptic seizure mining via novel empirical wavelet feature with J48 and KNN classifier;gallbladder shape estimation using tree-seed optimization tuned radial basis function network for assessment of acute cholecystitis;materialized view selection using backtracking search optimization algorithm;fractal coding for texture, satellite, and gray scale images to reduce searching time and complexity;Hybrid genetic algorithm–differential evolution approach for localization in WSN;local tetra pattern-based fruit grading using different classifiers;an integrated approach incorporating nonlinear dynamics and machine learning for predictive analytics and delving causal interaction;Image encryption based on arnold cat map and GA operator;Content-aware reversible data hiding: URHS.

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