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检索条件"任意字段=Proceedings of the 2020 9th International Conference on Computing and Pattern Recognition"

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Content-centric computing in visual systems 9th

引用

9th international conference on Image Analysis and Processing, ICIAP 1997

作者： Jain, Ramesh Center for Information Engineering Electrical and Computer Engineering University of California San Diego La JollaCA United States

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Intelligent Decision Technologies 2016 1st ed. 2016

引用

丛书名： Smart Innovation, Systems and Technologies

2016年

作者： Ireneusz Czarnowski Alfonso Mateos Caballero Robert J. Howlett Lakhmi C. Jain

ISBN: (数字)9783319396279

ISBN: (纸本)9783319396262

the KES-IDT-2016 proceedings give an excellent insight into recent research, both theoretical and applied, in the field of intelligent decision making. the range of topics explored is wide, and covers methods of grouping, classification, prediction, decision support, modelling and many more in such areas as finance, linguistics, medicine, management and transportation. this proceedings contain several sections devoted to specific topics, such as: Specialized Decision Techniques for Data Mining, Transportation and Project Management pattern recognition for Decision Making Systems New Advances of Soft computing in Industrial and Management Engineering Recent Advances in Fuzzy Systems Intelligent Data Analysis and Applications Reasoning-based Intelligent Systems Intelligent Methods for Eye Movement Data Processing and Analysis Intelligent Decision Technologies for Water Resources Management Intelligent Decision Making for Uncertain Unstructured Big Data Decision Making theory for Economics Interdisciplinary Approaches in Business Intelligence Research and Practice pattern recognition in Audio and Speech Processing the KES-IDT conference is a well-established international annual conference, interdisciplinary in nature. these two volumes of proceedings form an excellent account of the latest results and outcomes of recent research in this leading-edge area.

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Parallel Approximate Multi-pattern Matching on Heterogeneous Cluster Systems

Parallel Approximate Multi-Pattern Matching on Heterogeneous...

引用

9th international conference on Parallel and Distributed computing, Applications and Technologies

作者： Zhong, Cheng Fan, Zeng Su, Defu Guangxi Univ Sch Comp & Elect & Informat Nanning 530004 Peoples R China

ISBN: (纸本)9780769534435

For the given multiple patterns and a text string, firstly, a perfect hash function is constructed, the patterns are transformed into the unique pairs of integer values in parallel by the perfect hash function, the corresponding integer values are stored in a global hash table, and a recursion expression for computing hash function value of the signatures of each sub-string of text is also proposed. Secondly based on divisible load principle, a linear programming model for the optimal text distribution strategy is created and a parallel approximate multi-pattern matching algorithm allowing one error is presented on the heterogeneous cluster system which processors have different computing speeds and distinct communication capabilities and different memory sizes by taking into account computation and communication startup time and using the assigned processor distribution order. the experimental results on the cluster system of heterogeneous personal computers show that the presented parallel algorithm is averagely 25% faster than that one using the even text distribution strategy, and it obtains a nearly linear speedup and good scalability.

关键词： pattern matching Concurrent computing Distributed computing Distribution strategy Clustering algorithms Linear programming Application software Computer errors Microcomputers Parallel algorithms

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An Approach to Determine & Apply Solutions to Solve Detected Problems in Restructured Deployment Models using First-order Logic 9

An Approach to Determine & Apply Solutions to Solve Detected...

引用

9th international conference on Cloud computing and Services Science (CLOSER)

作者： Saatkamp, Karoline Breitenbuecher, Uwe Falkenthal, Michael Harzenetter, Lukas Leymann, Frank Univ Stuttgart Inst Architecture Applicat Syst Univ Str 38 D-70569 Stuttgart Germany

ISBN: (纸本)9789897583650

New paradigms such as edge computing opened up new opportunities for distributing applications to meet use-case-specific requirements. For automating the deployment of applications, deployment models can be created that describe the application structure with its components and their relations. However, the distribution is often not known in advance and, thus, deployment models have to be restructured. this can result in problems that have not existed before, e.g., components previously deployed in the same network were distributed, but security mechanisms are missing. Architecture patterns can be used to detect such problems, however, patterns describe only generic technology-independent solutions, which cannot automatically be applied to applications. Several concrete technologies exist that implements the pattern. Which solutions are applicable to a particular application is determined by, e.g., its hosting environment or used communication protocol. However, the manual effort to determine and implement appropriate solutions is immense. In this work, we present an approach to automate (i) the determination of solutions for an application using first-order logic and (ii) the adaptation of its deployment model accordingly. To validate the practical feasibility, we present a prototype using the cloud standard TOSCA and the logic programming language PROLOG.

关键词： Deployment Model pattern Logic Programming pattern-based Solution Model Adaptation TOSCA

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An Ethical Framework for Guiding the Development of Affectively-Aware Artificial Intelligence 9

An Ethical Framework for Guiding the Development of Affectiv...

引用

9th international conference on Affective computing and Intelligent Interaction (ACII)

作者： Ong, Desmond C. Natl Univ Singapore Dept Informat Syst & Analyt Singapore Singapore Agcy Sci Technol & Res Inst High Performance Comp Singapore Singapore

ISBN: (纸本)9781665400190

the recent rapid advancements in artificial intelligence research and deployment have sparked more discussion about the potential ramifications of socially- and emotionally-intelligent AI. the question is not if research can produce such affectively-aware AI, but when it will. What will it mean for society when machines-and the corporations and governments they serve-can "read" people's minds and emotions? What should developers and operators of such AI do, and what should they not do? the goal of this article is to pre-empt some of the potential implications of these developments, and propose a set of guidelines for evaluating the (moral and) ethical consequences of affectively-aware AI, in order to guide researchers, industry professionals, and policy-makers. We propose a multi-stakeholder analysis framework that separates the ethical responsibilities of AI Developers vis-a-vis the entities that deploy such AI-which we term Operators. Our analysis produces two pillars that clarify the responsibilities of each of these stakeholders: Provable Beneficence, which rests on proving the effectiveness of the AI, and Responsible Stewardship, which governs responsible collection, use, and storage of data and the decisions made from such data. We end with recommendations for researchers, developers, operators, as well as regulators and law-makers.

关键词： Ethics Affective computing Facial Emotion recognition Deep Learning

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Investigation and ordinal modelling of vocal features for stress detection in speech 9

Investigation and ordinal modelling of vocal features for st...

引用

9th international conference on Affective computing and Intelligent Interaction (ACII)

作者： Kalatzantonakis-Jullien, George-Marios Stefanakis, Nikolaos Giannakakis, Giorgos Hellen Open Univ Sch Sci & Technol Patras Greece Hellen Mediterranean Univ Dept Mus Technol & Acoust GR-74100 Rethimnon Greece Fdn Res & Technol Hellas FORTH Inst Comp Sci Iraklion Greece Hellen Mediterranean Univ Univ Res Ctr Inst AgriFood & Life Sci Iraklion Greece

ISBN: (纸本)9781665400190

this paper investigates a robust and effective automatic stress detection model based on human vocal features. Our study experimental dataset contains the voices of 58 Greek-speaking participants (24 male, 34 female, 26.9 +/- 4.8 years old), both in neutral and stressed conditions. We extracted a total of 76 speech-derived features after extensive study of the relevant literature. We investigated and selected the most robust features using automatic feature selection methods, comparing multiple feature ranking methods (such as RFE, mRMR, stepwise fit) to assess their pattern across gender & experimental phase factors. then, classification was performed both for the entire dataset, and then for each experimental task, for both genders combined and separately. the performance was evaluated using 10-fold cross-validation on the speakers. Our analysis achieved a best classification accuracy of 84.8% using linear SVM for the social exposure phase and 74.5% for the mental tasks phase using the gaussian SVM classifier. the ordinal modelling improved significantly our results, yielding a best on-subject basis 10-fold cross-validation classification accuracy of 95.0% for social exposure using gaussian SVM and 85.9% for mental tasks using the gaussian SVM. From our analysis, specific vocal features were identified as being robust and relevant to stress along with parameters to construct the stress model. However, it is was observed the susceptibility of speech to bias and masking and thus the need for universal speech markers for stress detection.

关键词： stress voice speech pairwise transformation Mel cepstral coefficients emotion recognition affective computing biosignals feature selection mRMR hyperparameter optimization

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SSRBC 2016: Sclera Segmentation and recognition Benchmarking Competition 9

SSRBC 2016: Sclera Segmentation and Recognition Benchmarking...

引用

9th international conference on Biometrics (ICB)

作者： Das, Abhijit Pal, Umapada Ferrer, Miguel A. Blumenstein, Michael Griffith Univ Inst Integrated & Intelligent Syst Griffith Qld Australia Indian Stat Inst Comp Vis & Pattern Recognit Unit Kolkata India Univ Las Palmas Gran Canaria IDeTIC Las Palmas Gran Canaria Spain Univ Technol Sydney Sch Software Sydney NSW Australia

ISBN: (纸本)9781509018697

this article reports and summarizes the results of a competition on sclera segmentation and recognition benchmarking, called Sclera Segmentation and recognition Benchmarking Competition 2016 (SSRBC 2016). It was organized in the context of the 9th IAPR international conference on Biometrics (ICB 2016). the goal of this competition was to record the recent developments in sclera segmentation and recognition, and also to gain the attention of researchers on this subject of biometrics. In this regard, we have used a multi-angle sclera dataset (NASD version 1). It is comprised of 2624 images taken from both the eyes of 82 identities. therefore, it consists of images of 164 (82*2) different eyes. We have prepared a manual segmentation mask of these images to create the baseline for both tasks. We have, furthermore, adopted precision and recall based statistical measures to evaluate the effectiveness of the segmentation and the ranks of the competing algorithms. the recognition accuracy measure has been employed to measure the recognition task. To summarize, twelve participants registered for the competition, and among them, three participants submitted their algorithms/systems for the segmentation task and two their recognition algorithm. the results produced by these algorithms reflect developments in the literature of sclera segmentation and recognition, employing cutting edge segmentation techniques. Along with the algorithms of three competing teams and their results, the NASD version 1 dataset will also be freely available for research purposes from the organizer's website. the competition also demonstrates the recent interests of researchers from academia as well as industry on this subject of biometrics.

关键词： Competition

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Natural Language Processing and Chinese computing 1

引用

丛书名： Lecture Notes in Computer Science

1000年

作者： Xiaodan Zhu Min Zhang Yu Hong Ruifang He

this two-volume set of LNAI 12340 and LNAI 12341 constitutes the refereed proceedings of the 9th CCF conference on Natural Language Processing and Chinese computing, NLPCC 2020, held in Zhengzhou, China, in October 2020.

ISBN: (数字)9783030604578

ISBN: (纸本)9783030604561

关键词： Artificial Intelligence Information Systems and Communication Service Computer Imaging, Vision, pattern recognition and Graphics theory of Computation Computer Appl. in Social and Behavioral Sciences

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the Apprentice Gaze - AR Experience on Serralves Museum 9

The Apprentice Gaze - AR Experience on Serralves Museum

引用

9th international conference on Digital and Interactive Arts (ARTECH)

作者： Silva, Manuel Assaf, Rodrigo Pollini, Denise Morais, Diogo Teixeira, Luis Univ Catolica Portuguesa Sch Arts Digital Creat Ctr Porto Portugal Fundacao Serralves Dept Educ Porto Portugal Univ Catolica Portuguesa Sch Arts Digital Creat Ctr CITAR Porto Portugal

ISBN: (纸本)9781450372503

Project CHIC(Cooperative Holistic View on Internet and Content) aims to develop a set of digital platforms, based on open formats and interoperable technologies that promote and increase the dynamics of Portuguese media content creation. One of the platforms is a georeferenced augmented reality platform capable of interconnecting and retaining different sources of information and users, with the objective of providing an application capable of generating contextual information about heritage and tourism, specifically attributed to a user and a concrete experience. this article presents the development of three augmented reality experiences within the context of a museum.

关键词： Art Museum Augmented Reality Mobile computing Interactive Exhibit Education

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Identification of Latin-based languages through character stroke categorization

Identification of Latin-based languages through character st...

引用

9th international conference on Document Analysis and recognition, ICDAR 2007

作者： Lu, Shijian Li, Linlin Chew, Lim Tan Department of Computer Science School of Computing National University of Singapore Kent Ridge 117543 Singapore Singapore

ISBN: (纸本)0769528228

this paper presents a language identification technique that detects Latin-based languages of imaged documents without OCR. the proposed technique detects languages through the word shape coding, which converts each word image into a word shape code and accordingly transforms each document image into an electronic document vector. For each Latin-based language under study, a language template is first constructed through a corpus-based learning process. the underlying language of the query document is then determined based on the similarity between the query document vector and multiple constructed language templates. Compared with the reported methods, the proposed language identification technique is fast, accurate, and tolerant to text segmentation error caused by noise and various types of document degradation. Experimental results show some promising results. © 2007 IEEE.

关键词： Natural language processing systems

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