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International Joint Conference on Neural Networks

作者： Fabian Sachara Finn Handmann Nico Cremer Thomas Kopinski Alexander Gepperth Uwe Handmann University of Applied Sciences Hochschule Ruhr West Lützowstrasse 5 46236 Bottrop Germany Fachhochschule Südwestfalen Lindenstra?e 52 59872 Meschede Germany Applied Computer Science University of Applied Sciences Fulda Germany

ISBN: (纸本)9781509061839

We present a new RGB-D database for multi-pose object recognition tasks. With the help of a multi-axis rotation framework, we are capable of capturing depth and color data of arbitrary small objects from virtually any viewpoint. In addition, recording is performed in a nearly lossless fashion, avoiding typical bleeding artifacts present in related reference data bases. This contribution presents the main advantages of our setup and contrasts it against other reference data bases. Furthermore, it outlines possible use cases and application scenarios of our data set and is complemented by experiments with standard machine learning techniques used in, e.g., object recognition tasks within the robotics domain. The experiments demonstrate the validity of our data base as they corroborate that viewpoint variance is indeed an important factor to take into account for object detection, which, from our perspective, is sometimes not considered at the required level. Detection accuracy is high if samples can be trained on data taking into account as many viewpoints as possible.

关键词： databases Cameras object recognition Image color analysis Robot sensing systems Algorithm design and analysis Three-dimensional displays database object recognition three-dimensional displays Algorithm design and analysis Manipulator sensing systems image colour analysis Cameras object database

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High-level data fusion component for drone classification and decision support in counter UAV 23

High-level data fusion component for drone classification an...

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Conference on Open Architecture/Open Business Model Net-Centric Systems and Defense Transformation

作者： Sander, Jennifer Kuwertz, Achim Muehlenberg, Dirk Mueller, Wilmuth Fraunhofer Inst Optron Syst Technol & Image Explo Fraunhoferstr 1 D-76131 Karlsruhe Germany

ISBN: (数字)9781510618145

ISBN: (纸本)9781510618145

Today, drone technology has been made available around the world. Anyone can purchase a drone from an online retailer. Government agencies and military are seeing a rise in drones used for terrorism, destruction and espionage. The emergence of threats caused by unfriendly or hostile drones requires proactive drone detection in order to decide on appropriate defensive actions. In this contribution, a high-level data fusion component for drone classification is presented. The high-level data fusion component is part of our counter UAV system MODEAS including decision support. The component provides well-defined interfaces which allow it to be integrated also into other counter UAV systems. The aim of the high-level data fusion component is to support an operator in his decision making by providing detailed information about detected drones together with assigned threat levels. To identify a detected and tracked drone with sufficient detail, a knowledge-based classification is performed, based on background knowledge like drone model specifications. By fusing the knowledge-based classification results with prior results of a sensor-based classification, the overall classification is improved. The fusion results, in addition to kinematic data, also contain specific capabilities of the respective drone like its maximum payload, endurance, and speed as well as recorded incidents with similar drones or their typical (commercial) usage, if known. Based on these fusion results, a threat analysis is performed. The component's output then is a ranked list of dossiers for the most probable types of drones with regard to the observation data and their assigned threat levels.

关键词： counter UAV MODEAS drone classification knowledge-based approach high-level data fusion decision support threat assessment behavior analysis object database STANAG 4559

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'Virtual museums' as digital collection complexes. A museological perspective using the example of Hans-Gross-Kriminalmuseum

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MUSEUM MANAGEMENT AND CURATORSHIP 2017年第3期32卷 281-297页

作者： Biedermann, Bernadette Karl Franzens Univ Graz Univ Graz Univ Museums Inst Hist Graz Austria

The term 'virtual museum' used in German-speaking areas is defined differently in various disciplines such as museology and digital humanities. In the museum context, it usually refers to all digital provisions of museum object data in the web. Digital sceptics worry about the aura and the loss of authenticity of the original object. This paper examines the significance of digital technologies for core museum tasks of collecting, investigating and mediating museum object data from the perspective of museology. It is based on the assumption that presentations of museum objects in a virtual space cannot compete with real museum exhibitions, as they cannot replace an encounter with the original object. Additionally, they serve as a medium in their own right. Virtually represented collection complexes can be used as an independent educational tool by linking multi-layered meanings of museum objects. These presuppositions are demonstrated using the example of a physical museum collection.

关键词： Museum documentation museology virtual museum museum computing object database museum and digital age

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Improving conceptual data models through iterative development

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DATA & KNOWLEDGE ENGINEERING 2015年 98卷 54-73页

作者： Zaeschke, Tilmann Leone, Stefania Gmuender, Tobias Norrie, Moira C. Swiss Fed Inst Technol Inst Informat Syst CH-8092 Zurich Switzerland Univ So Calif CS Dept Semant Informat Res Lab Los Angeles CA 90089 USA

Agile methods promote iterative development with short cycles, where user feedback from the previous iteration is used to refactor and improve the current version. To facilitate agile development of information systems, this paper offers three contributions. First, we introduce the concept of evolvability as a model quality characteristic. Evolvability refers to the expected implications of future model refactorings, both in terms of complexity of the required database evolution algorithm and in terms of the expected volume of data to evolve. Second, we propose extending the agile development cycle by using database profiling information to suggest adaptations to the conceptual model to improve performance. For every software release, the database profiler identifies and analyses navigational access patterns, and proposes model optimisations based on data characteristics, access patterns and a cost-benefit model. Based on an experimental evaluation of the profiler we discuss why the quality of conceptual models can generally benefit from profiling and how performance measurements convey semantic information. Third, we discuss the flow of semantic information when developing and using information systems. Beyond these contributions, we also make a case for using object databases in agile development environments. However, most of the presented concepts are also applicable to other database paradigms. (C) 2015 Elsevier B.V. All rights reserved.

关键词： database profiling Evolvability object database Agile development Conceptual models Model quality Semantic verification

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Keyframe-based online object learning and detection

Keyframe-based online object learning and detection

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IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Sehyung Lee Jongwoo Lim Il Hong Suh Department of Electronics and Computer Engineering Hanyang University Seoul Korea Division of Computer Science and Engineering Hanyang university Seoul Korea

ISBN: (纸本)9781509037636

In this paper, we propose a keyframe-based online object learning and detection method. To manage appearance changes of target objects, the proposed method incrementally updates an object database using detection results. One of the major problems in updating the appearance model is that the object model can gradually be degraded by accumulated errors and biased to specific views. To solve this problem, our object model is updated according to the selected keyframes, which not only help memorize important views of target objects, but also prevent the holistic appearance model from overfitting. The database is represented as a graph of the registered images, and the importance of the database images is measured by analyzing the constructed graph. Then, the redundant or less important images are discarded from the database. As a result, the database is efficiently maintained while new views of the objects are gradually added. The experimental results demonstrate that the proposed algorithm efficiently maintains the object database and improves the detection performance compared to previous incremental object learning and detection algorithms.

关键词： database object database visual databases object information model Detection algorithms inspection methods

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Optimising Conceptual Data Models through Profiling in object databases

Optimising Conceptual Data Models through Profiling in Objec...

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32nd International Conference on Conceptual Modeling (ER)

作者： Zaeschke, Tilmann Leone, Stefania Gmuender, Tobias Norrie, Moira C. ETH Inst Informat Syst CH-8092 Zurich Switzerland Univ Southern Calif Semant Informat Res Lab Los Angeles CA 90089 USA

ISBN: (纸本)9783642419249

Agile methods promote iterative development with short cycles, where user feedback from the previous iteration is used to refactor and improve the current version. For information systems development, we propose to extend this feedback loop by using database profiling information to propose adaptations to the conceptual model to improve performance. For every software release, our database profiler identifies and analyses navigational access patterns, and proposes model optimisations based on data characteristics, access patterns and a cost-benefit model. The proposed model optimisations are based on common database and data model refactoring patterns. The database profiler has been implemented as part of an open-source object database and integrated into an existing agile development environment, where the model optimisations are presented as part of the IDE. We evaluate our approach based on an example of agile development of a research publication system.

关键词： database profiling object database model optimisation

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The Storage System for a Multimedia Data Manager Kernel 14

The Storage System for a Multimedia Data Manager Kernel

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14th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT)

作者： Valencio, Carlos Roberto de Almeida, Fabio Renato Machado, Jose Marcio Colombini, Angelo Cesar Neves, Leandro Alves Gratao de Souza, Rogeria Cristiane Sao Paulo State Univ UNESP Dept Ciencias Comp & Estat Sao Paulo Brazil Fed Univ Sao Carlos UFSCar Dept Comp Sao Paulo Brazil

ISBN: (纸本)9781479924189

One way to boost the performance of a database Management System (DBMS) is by fetching data in advance of their use, a technique known as prefetching. However, depending on the resource being used (file, disk partition, memory, etc.), the way prefetching is done might be different or even not necessary, forcing a DBMS to be aware of the underlying Storage System. In this paper we propose a Storage System that frees the DBMS of this task by exposing the database through a unique interface, no matter what kind of resource hosts it. We have implemented a file resource that recognizes and exploits sequential access patterns that emerge over time to prefetch adjacent blocks to the requested ones. Our approach is speculative because it considers past accesses, but it also considers hints from the upper layers of the DBMS, which must specify the access context in which a read operation takes place. The informed access context is then mapped to one of the available channels in the file resource, which is equipped with a set of internal buffers, one per channel, for the management of fetched and prefetched data. Prefetched data are moved to the main cache of the DBMS only if really requested by the application, which helps to avoid cache pollution. So, we slightly introduced a two level cache hierarchy without any intervention of the DBMS kernel. We ran the tests with different buffer settings and compared the results against the OBL policy, which showed that it is possible to get a read time up to two times faster in a highly concurrent environment without sacrificing the performance when the system is not under intensive workloads.

关键词： Access context buffer management cache pollution channel database management system multimedia database object database performance prefetching sequential access pattern storage system

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Measuring and modelling the performance of a parallel ODMG compliant object database server

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CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE 2006年第1期18卷 63-109页

作者： Sampaio, SDM Paton, NW Smith, J Watson, P Univ Manchester Dept Comp Sci Manchester M13 9PL Lancs England Newcastle Univ Dept Comp Sci Newcastle Upon Tyne NE1 7RU Tyne & Wear England

object database management systems (ODBMSs) are now established as the database management technology of choice for a range of challenging data intensive applications. Furthermore, the applications associated with object databases typically have stringent performance requirements, and some are associated with very large data sets. An important feature for the performance of object databases is the speed at which relationships can be explored. In queries, this depends on the effectiveness of different join algorithms into which queries that follow relationships can be compiled. This paper presents a performance evaluation of the Polar parallel object database system, focusing in particular on the performance of parallel join algorithms. Polar is a parallel, shared-nothing implementation of the object database Management Group (ODMG) standard for object databases. The paper presents an empirical evaluation of queries expressed in the ODMG Query Language (OQL), as well as a cost model for the parallel algebra that is used to evaluate OQL queries. The cost model is validated against the empirical results for a collection of queries using four different join algorithms, one that is value based and three that are pointer based. Copyright (c) 2005 John Wiley & Sons, Ltd.

关键词： object database parallel databases ODMG OQL benchmark cost model

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A novel Method to Construct Visual Vocabulary Based on Maximization of Mutual Information

A novel Method to Construct Visual Vocabulary Based on Maxim...

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International Conference on Artificial Intelligence and Computational Intelligence

作者： Guo Li-Jun Zhao Jie-Yu Zhang Rong Chinese Acad Sci Inst Comp Technol Beijing 100080 Peoples R China Grad Univ Chinese Acad Sci Beijing 100039 Peoples R China Ningbo Univ Fac Informat Sci & Engn Ningbo 315211 Zhejiang Peoples R China

ISBN: (纸本)9780769538167

Bag of visual words model has shown interesting capabilities of object category recognition. Considering that there is different discriminative ability of each visual word for object categorization, we propose a novel method based on maximization of mutual information to measure the discriminative ability of words and then give a visual vocabulary optimization algorithm based on more discriminative words selection. Experiments showed that the method presented in the paper not only preserves more discriminative information and gives a further 7.9% classification performance increase over standard vocabulary, but also result in dimension reduction in large scale and classification efficiency increase. The experiments were performed on a 7-class object database containing 1776 images.

关键词： classification efficiency Optimization algorithms object database Visualization Word Vocabulary Bag device

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An efficient storage model for the SBML documents using object databases

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1st International Workshop on Data Mining and Bioinformatics

作者： Jung, Seung-Hyun Jung, Tae-Sung Kim, Tae-Kyung Kim, Kyoung-Ran Yoo, Jae-Soo Cho, Wan-Sup Chungbuk Natl Univ Dept Management Informat Syst Chungbuk 361763 South Korea Chungbuk Natl Univ Dept Informat Ind Engn Chungbuk 361763 South Korea Chungbuk Natl Univ Dept Comp & Commun Engn Chungbuk 361763 South Korea

ISBN: (纸本)9783540689706

As SBML is regarded as a de-facto standard to express the biological network data in systems biology, the amount of the SBML documents is exponentially increasing. We propose an SBML data management system (SMS) on top of an object database. Since the object database supports abundant data types like multi-valued attributes and object references, mapping from the SBML documents into the object database is straightforward. We adopt the event-based SAX parser instead of the DOM parser for dealing with huge SBML documents. Note that DOM parser suffers from excessive memory overhead for the document parsing. For high quality data, SMS supports data cleansing function by using gene ontology. Finally, SMS generates user query results in an SBML format (for data exchange) or in a visual graphs (for intuitive understanding). Real experiments show that our approach is superior to the one using conventional relational databases in the aspects of the modeling capability, storage requirements, and data quality.

关键词： SBML object database bioinformatics ontology pathway system biology

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