检索结果-内蒙古大学图书馆

6th Collaborative European research Conference, CERC 2020

作者： Below, Nicola Burkhardt, Dirk Kaupp, Lukas Nazemi, Kawa Darmstadt University of Applied Sciences Human-Computer Interaction and Visual Analytics Group Germany

Analytical Reasoning by applying machine learning approaches, artificial intelligence, NLP and visualizations allow to get deep insights into the different domains of various stakeholders and enable to solve complex tasks. Thereby the tasks are very heterogenous and subject of investigation in the different areas of application. These tasks or challenges should be defined by the stakeholders themselves and lead through a deep investigation to advanced analytical approaches. We therefore set up a strategic alliance of research, enterprises and societal organization with the goal of a strong collaboration to identify in a first step these challenges and workout technological solutions for each application scenario. We give in this paper a first draft of current challenges and technological advancements. The main contribution of this paper is next to an accurate description of the current challenges in the analytics domain, also the description of an agenda how these challenges can be solved. Furthermore, a process is explained, how the strategic alliance should act and organize their work to realize beneficial and useful analytical solutions. Copyright © 2020 for this paper by its authors.

关键词： Artificial intelligence

来源：评论

学校读者我要写书评

暂无评论

visual dashboards in trend analytics to observe competitors and leading domain experts 6

Visual dashboards in trend analytics to observe competitors ...

引用

6th Collaborative European research Conference, CERC 2020

作者： Sina, Lennart Burkhardt, Dirk Nazemi, Kawa Darmstadt University of Applied Sciences Human-Computer Interaction and Visual Analytics Group Germany

The rapid change due to digitalization challenge a variety of market players and force them to find strategies to be aware of developments in these markets, particularly those that impact their business. The main challenge is what a practical solution could look like and how technology can support market players in these trend observation tasks. The paper outlines therefore a technological solution to observe specific authors e.g. researchers who influence a certain market or engineers of competitors. In many branches both are well-known groups to market players and there is almost always the need of a technology that supports the topical observation. This paper focuses on the concept of how a visual dashboard could enable a market observation and how data must be processed for it and its prototypical implementation which enables an evaluation later. Furthermore, the definition of a principal technological analysis for innovation and technology management is created and is also an important contribution to the scientific community that specifically considers the technology perspective and its corresponding requirements. Copyright © 2020 for this paper by its authors.

关键词： Commerce

来源：评论

学校读者我要写书评

暂无评论

A mobile visual analytics approach for instant trend analysis in mobile contexts 5

A mobile visual analytics approach for instant trend analysi...

引用

5th International Conference of the Virtual and Augmented Reality in Education, VARE 2019

作者： Burkhardt, Dirk Nazemi, Kawa Kuijper, Arjan Ginters, Egils Human-Computer Interaction and Visual Analytics Research Group Darmstadt University of Applied Sciences Darmstadt Germany Department of Computer Science TU Darmstadt Darmstadt Germany Riga Technical University Riga Latvia

ISBN: (纸本)9788885741423

The awareness of market trends becomes relevant for a broad number of market branches, in particular the more they are challenged by the digitalization. Trend analysis solutions help business executives identifying upcoming trends early. But solid market analysis takes their time and are often not available on consulting or strategy discussions. This circumstance often leads to unproductive debates where no clear strategy, technology etc. could be identified. Therefore, we propose a mobile visual trend analysis approach that enables a quick trend analysis to identify at least the most relevant and irrelevant aspects to focus debates on the relevant options. To enable an analysis like this, the exhausting analysis on powerful workstations with large screens has to adopted to mobile devices within a mobile behavior. Our main contribution is the therefore a new approach of a mobile knowledge cockpit, which provides different analytical visualizations within and intuitive interaction design. © 5th International Conference of the Virtual and Augmented Reality in Education, VARE 2019. All rights reserved.

关键词： Decision support systems

来源：评论

学校读者我要写书评

暂无评论

News Ninja: Gamified Annotation of Linguistic Bias in Online News

引用

Proceedings of the ACM on human-computer interaction 2024年第CHI PLAY期8卷 1-29页

作者： Hinterreiter, Smi Spinde, Timo Oberdörfer, Sebastian Echizen, Isao Latoschik, Marc Erich Human-Computer Interaction Group University of Würzburg Würzburg Germany Scientific Information Analytics Group University of Göttingen Göttingen Germany Information and Society Research Division National Institute of Informatics Tokyo Japan

Recent research shows that visualizing linguistic bias mitigates its negative effects. However, reliable automatic detection methods to generate such visualizations require costly, knowledge-intensive training data. To facilitate data collection for media bias datasets, we present News Ninja, a game employing data-collecting game mechanics to generate a crowdsourced dataset. Before annotating sentences, players are educated on media bias via a tutorial. Our findings show that datasets gathered with crowdsourced workers trained on News Ninja can reach significantly higher inter-annotator agreements than expert and crowdsourced datasets with similar data quality. As News Ninja encourages continuous play, it allows datasets to adapt to the reception and contextualization of news over time, presenting a promising strategy to reduce data collection expenses, educate players, and promote long-term bias mitigation. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Data collection

来源：评论

学校读者我要写书评

暂无评论

Total cluster: A person agnostic clustering method for broadcast videos 14

Total cluster: A person agnostic clustering method for broad...

引用

9th Indian Conference on computer Vision, Graphics and Image Processing, ICVGIP 2014

作者： Tapaswi, Makarand Parkhi, Omkar M. Rahtu, Esa Sommerlade, Eric Stiefelhagen, Rainer Zisserman, Andrew Computer Vision for Human Computer Interaction Karlsruhe Institute of Technology Germany Visual Geometry Group Department of Engineering Science University of Oxford United Kingdom Center for Machine Vision Research University of Oulu Finland

ISBN: (纸本)1595930361

The goal of this paper is unsupervised face clustering in edited video material - where face tracks arising from different people are assigned to separate clusters, with one cluster for each person. In particular we explore the extent to which faces can be clustered automatically without making an error. This is a very challenging problem given the variation in pose, lighting and expressions that can occur, and the similarities between different people. The novelty we bring is three fold: first, we show that a form of weak supervision is available from the editing structure of the material - the shots, threads and scenes that are standard in edited video;second, we show that by first clustering within scenes the number of face tracks can be significantly reduced with almost no errors;third, we propose an extension of the clustering method to entire episodes using exemplar SVMs based on the negative training data automatically harvested from the editing structure. The method is demonstrated on multiple episodes from two very different TV series, Scrubs and Buffy. For both series it is shown that we move towards our goal, and also outperform a number of baselines from previous works. Copyright is held by the authors.

关键词： Cluster analysis

来源：评论

学校读者我要写书评

暂无评论

The concept of augmented reality application for putting alignment in golf 5

The concept of augmented reality application for putting ali...

引用

5th International Conference of the Virtual and Augmented Reality in Education, VARE 2019

作者： Ginters, Egils Burkhardt, Dirk Nazemi, Kawa Merkuryev, Yuri Sociotechnical Systems Engineering Group Department of Modelling and Simulation Faculty of Computer Science and Information Technology Riga Technical University 2 Daugavgrivas Street RigaLV-1048 Latvia Sociotechnical Systems OU Sakala 7-2 Street Tallinn10141 Estonia Human-Computer Interaction and Visual Analytics Research Group Darmstadt University of Applied Sciences Darmstadt Germany

ISBN: (纸本)9788885741423

Virtual and augmented reality (VR / AR) applications have successfully overcome the critical part of the Gartner curve. Investments are made and new products entering the economy. However, a very small percentage of society have also heard about AR glasses, mainly linking these with potential identity threats and personal data breaches. The authors dealt with the design of application of AR to improve golf skills by improving the putting technique. The above solution is complicated by requiring complex object recognition, tracking and advanced AR software designing. © 5th International Conference of the Virtual and Augmented Reality in Education, VARE 2019. All rights reserved.

关键词： Augmented reality

来源：评论

学校读者我要写书评

暂无评论

visualizing Query Occurrence in Mobile Web Search Interfaces

Visualizing Query Occurrence in Mobile Web Search Interfaces

引用

International Conference on Information visualisation (IV)

作者： Tomi Heimonen Harri Siirtola Tampere Unit for Computer-Human Interaction (TAUCHI) Visual Interaction Research Group Department of Computer Sciences University of Tampere Finland

Mobile Web search engines represent retrieved results using primarily text based result surrogates. Users could benefit from information visualization techniques that provide more information about the results as basis of relevance judgments. We present a query-biased visualization approach that incorporates query occurrence visualization into the conventional mobile Web search interface. Textual and graphical versions of the design were evaluated in a study with 18 users. Eleven of the participants preferred either one of the visualizations to the traditional search interface. The results suggest that the key benefit of the proposed visualization is its unobtrusiveness. It does not distract from normal use yet when necessary it can be used to help with relevance assessment, for example when the search engine fails to provide good result ***, the utility of the proposed query occurrence visualization is dependent on how well it matches the user's mental model and existing search strategies.

关键词： Web search Search engines Mobile computing computer interfaces Data visualization Frequency Cellular neural networks Information retrieval Cognitive science Web pages

来源：评论

学校读者我要写书评

暂无评论

Innovations in Mobility and Logistics: Assistance of Complex Analytical Processes in visual Trend analytics

Innovations in Mobility and Logistics: Assistance of Complex...

引用

International Scientific Conference on Information Technology and Management Science of Riga Technical University (ITMS)

作者： Dirk Burkhardt Kawa Nazemi Egils Ginters Human-Computer Interaction and Visual Analytics group Darmstadt University of Applied Sciences Darmstadt Germany Riga Technical University Riga Latvia

ISBN: (数字)9781728191058

ISBN: (纸本)9781728191065

A variety of new technologies and ideas for businesses are arising in the domain of logistics and mobility. It can be differentiated between fundamental new approaches, e.g. central packaging stations or deliveries via drones and minor technological advancements that aim on more ecologically and economic transportation. The need for analytical systems that enable identifying new technologies, innovations, business models etc. and give also the opportunity to rate those in perspective of business relevance is growing. The users' behavior is commonly investigated in adaptive systems, which is considering the individual preferences of users, but neglecting often the tasks and goals of the analysis. A process-related supports could assist to solve an analytical task in a more efficient and effective way. We introduce in this paper an approach that enables non-professionals to perform visual trend analysis through an advanced process assistance based on process mining and visual adaptation. This allows generating a process model based on events, which is the baseline for process support feature calculation. These features in form of visual adaptations and the process model enable assisting non-experts in complex analytical tasks.

关键词： Market research Task analysis Business Adaptation models Analytical models Data mining Data visualization

来源：评论

学校读者我要写书评

暂无评论

"The support needs to be part of the system": designing inclusive eHealth applications for older adults with low eHealth literacy

"The support needs to be part of the system": designing incl...

引用

2022 Engaging Citizen Science Conference, CitSci 2022

作者： Prinzellner, Yvonne Simon, Ali Drachmann, Danielle Werner, Katharina Münter, Lars Bulsink, Vera Smits, Carolien Fitzpatrick, Geraldine Schwaninger, Isabel Johanniter Österreich Ausbildung und Forschung Gemeinnützige GmbH Ignaz-Köck-Straße 22 Vienna1210 Austria Danish Committee for Health Education Classensgade 71 5. Sal Copenhagen2100 Denmark TU Wien Institute of Visual Computing and Human-Centered Technology Human Computer Interaction Group Argentinierstraße 8 Vienna1040 Austria Roessingh Research and Development Roessinghsbleekweg 33b Enschede7522 Netherlands Arthur van Schendelstraat 600 Utrecht3511 MJ Netherlands

In the project "Got-IT", an online toolkit was developed to assist with the design of inclusive eHealth solutions targeting the promotion of healthy lifestyles among older adults (65+) with low eHealth literacy. The project consortium has used participatory citizen science as an approach to actively engage with the relevant stakeholders, including older adults with low eHealth literacy, eHealth developers, and secondary end users like eHealth professionals. We applied three different research designs, all centered on the active engagement of the different stakeholders, using the design of an eHealth app to ground the investigations. The outcomes of the Got-IT project align not only with the first objective of the AAL Programme ("better quality of life for older adults and their networks, by empowering the citizens to take care of their own health") but are also central components of citizen science as a whole, by actively engaging the different target groups at various levels of our research process. © Copyright owned by the author(s) under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0)

关键词：

来源：评论

学校读者我要写书评

暂无评论

Why is the Winner the Best?

Why is the Winner the Best?

引用

Conference on computer Vision and Pattern Recognition (CVPR)

作者： M. Eisenmann A. Reinke V. Weru M. D. Tizabi F. Isensee T. J. Adler S. Ali V. Andrearczyk M. Aubreville U. Baid S. Bakas N. Balu S. Bano J. Bernal S. Bodenstedt A. Casella V. Cheplygina M. Daum M. De Bruijne A. Depeursinge R. Dorent J. Egger D. G. Ellis S. Engelhardt M. Ganz N. Ghatwary G. Girard P. Godau A. Gupta L. Hansen K. Harada M. Heinrich N. Heller A. Hering A. Huaulmé P. Jannin A. E. Kavur O. Kodym M. Kozubek J. Li H. Li J. Ma C. Martín-Isla B. Menze A. Noble V. Oreiller N. Padoy S. Pati K. Payette T. Rädsch J. Rafael-Patiño V. Singh Bawa S. Speidel C. H. Sudre K. Van Wijnen M. Wagner D. Wei A. Yamlahi M. H. Yap C. Yuan M. Zenk A. Zia D. Zimmerer D. Aydogan B. Bhattarai L. Bloch R. Brüngel J. Cho C. Choi Q. Dou I. Ezhov C. M. Friedrich C. Fuller R. R. Gaire A. Galdran Á. García Faura M. Grammatikopoulou S. Hong M. Jahanifar I. Jang A. Kadkhodamohammadi I. Kang F. Kofler S. Kondo H. Kuijf M. Li M. Luu T. Martinčič P. Morais M. A. Naser B. Oliveira D. Owen S. Pang J. Park S. Park S. Płotka E. Puybareau N. Rajpoot K. Ryu N. Saeed A. Shephard P. Shi D. Štepec R. Subedi G. Tochon H. R. Torres H. Urien J. L. Vilaça K. A. Wahid H. Wang J. Wang L. Wang X. Wang B. Wiestler M. Wodzinski F. Xia J. Xie Z. Xiong S. Yang Y. Yang Z. Zhao K. Maier-Hein P. F. Jäger A. Kopp-Schneider L. Maier-Hein Division of Intelligent Medical Systems German Cancer Research Center (DKFZ) Heidelberg Germany Helmholtz Imaging German Cancer Research Center (DKFZ) Heidelberg Germany Faculty of Mathematics and Computer Science Heidelberg University Heidelberg Germany Division of Biostatistics German Cancer Research Center (DKFZ) Heidelberg Germany Division of Medical Image Computing German Cancer Research Center (DKFZ) Heidelberg Germany Faculty of Engineering and Physical Sciences School of Computing University of Leeds Leeds UK Institute of Informatics School of Management HES-SO Valais-Wallis University of Applied Sciences and Arts Western Switzerland Sierre Switzerland Department of Nuclear Medicine and Molecular Imaging Lausanne University Hospital Lausanne Switzerland Technische Hochschule Ingolstadt Ingolstadt Germany Center for Artificial Intelligence and Data Science for Integrated Diagnostics (AI2D) and Center for Biomedical Image Computing and Analytics (CBICA) University of Pennsylvania Philadelphia PA USA Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania Philadelphia PA USA Department of Radiology Perelman School of Medicine University of Pennsylvania Philadelphia PA USA Department of Radiology University of Washington Seattle WA USA Department of Computer Science Wellcome/EPSRC Centre for Interventional and Surgical Sciences (WEISS) University College London London UK Universitat Autònoma de Barcelona & Computer Vision Center Barcelona Spain Division of Translational Surgical Oncology National Center for Tumor Diseases (NCT/UCC) Dresden Dresden Germany Department of Advanced Robotics Istituto Italiano di Tecnologia Italy Department of Electronics Information and Bioengineering Politecnico di Milano Milan Italy IT University of Copenhagen Copenhagen Denmark Department of General Visceral and Transplantation Surgery Heidelberg University Hospital Heidelberg Germany Department of Radiology and Nuc

International benchmarking competitions have become fundamental for the comparative performance assessment of image analysis methods. However, little attention has been given to investigating what can be learnt from these competitions. Do they really generate scientific progress? What are common and successful participation strategies? What makes a solution superior to a competing method? To address this gap in the literature, we performed a multicenter study with all 80 competitions that were conducted in the scope of IEEE ISBI 2021 and MICCAI 2021. Statistical analyses performed based on comprehensive descriptions of the submitted algorithms linked to their rank as well as the underlying participation strategies revealed common characteristics of winning solutions. These typically include the use of multi-task learning (63%) and/or multi-stage pipelines (61%), and a focus on augmentation (100%), image preprocessing (97%), data curation (79%), and post-processing (66%). The “typical” lead of a winning team is a computer scientist with a doctoral degree, five years of experience in biomedical image analysis, and four years of experience in deep learning. Two core general development strategies stood out for highly-ranked teams: the reflection of the metrics in the method design and the focus on analyzing and handling failure cases. According to the organizers, 43% of the winning algorithms exceeded the state of the art but only 11% completely solved the respective domain problem. The insights of our study could help researchers (1) improve algorithm development strategies when approaching new problems, and (2) focus on open research questions revealed by this work.

关键词：

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：