48 research outputs found

    A Computational Neuroscience Approach to Higher-Order Texture Perception

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    Natural images contain large amounts of structural information characterised by higher-order spatial correlations. Neurons have limited capacities, so the visual system must filter out non-salient information, but retain that which is behaviourally relevant. Previous research has concentrated on two-point correlations; there has been less research into higher-order correlations, although the visual system is sensitive to them. Isotrigon textures can be used for this purpose. Their salient structure is exclusively due to fourth- and higher-order spatial correlations and they have the same structural features that create salience in natural images. In Chapter 2, we evaluated human texture discrimination using 10 novel isotrigon textures (VnL2) and 17 standard V3L2 isotrigon textures. Factor analysis revealed that as few as 3 mechanisms may govern the detection of fourth- and higher-order image structure. The Maddess group has previously published evidence that the number of independent mechanisms is less than 10 and perhaps as small as 3-4. The computation of higher-order correlations by the brain is neuro-physiologically plausible via nonlinear combinations of recursive and/or rectifying processes. In Chapter 3, we utilised the crowdsourcing platform “mTurk” to implement a large texture discrimination study. Under laboratory conditions, we showed that the testing modality was robust across a range of browsers, resolutions, contrasts and screen sizes. Texture discrimination data was gathered from 121 naïve subjects and compared to 2 independent laboratory data sets. Factor analysis indicated the presence of 3-4 factors, consistent with previous studies. Based on Pearson's correlation and coefficients of repeatability, mTurk is capable of producing data of comparable quality to laboratory studies. This is significant as mTurk has not previously been systematically evaluated for visual psychometric research. In Chapter 4, we employed a set of statistically controlled ternary textures. The textures were constrained (spatial correlations from 1st to 4th order) and their salience could be independently controlled by the addition of noise. To the ideal observer, all textures defined by a given amount of noise are equally detectable. However, humans are not ideal observers; their visual perceptual resources are restricted. Because of the number of textures available, we used mTurk to gather performance functions from 928 subjects for a subset of the texture space. Perceptual salience varied for each image statistic, with rank order: gamma > beta_hv > beta_diag > alpha > theta. This supports the order previously published for the related binary stochastic textures. The two least salient directions were consistently white:black and grey-bias (for gammas and betas), and black:grey and grey:white (for thetas and alphas). Such differences reflect the sensitivities and limitations of neural processing and are a manifestation of efficient coding. We hypothesised that the grey token conferred non-salience. Indeed, for gammas and betas, the grey-bias was consistently the second least salient. However, this did not hold for thetas or alphas. Counter-intuitively, the order of texture presentation did not significantly affect discrimination performance. An analysis of 31 repeat Workers found evidence of learning for beta textures, whereas performance for other textures was already maximal. This thesis concludes by considering future research

    Proceedings der 11. Internationalen Tagung Wirtschaftsinformatik (WI2013) - Band 1

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    The two volumes represent the proceedings of the 11th International Conference on Wirtschaftsinformatik WI2013 (Business Information Systems). They include 118 papers from ten research tracks, a general track and the Student Consortium. The selection of all submissions was subject to a double blind procedure with three reviews for each paper and an overall acceptance rate of 25 percent. The WI2013 was organized at the University of Leipzig between February 27th and March 1st, 2013 and followed the main themes Innovation, Integration and Individualization.:Track 1: Individualization and Consumerization Track 2: Integrated Systems in Manufacturing Industries Track 3: Integrated Systems in Service Industries Track 4: Innovations and Business Models Track 5: Information and Knowledge ManagementDie zweibĂ€ndigen TagungsbĂ€nde zur 11. Internationalen Tagung Wirtschaftsinformatik (WI2013) enthalten 118 ForschungsbeitrĂ€ge aus zehn thematischen Tracks der Wirtschaftsinformatik, einem General Track sowie einem Student Consortium. Die Selektion der Artikel erfolgte nach einem Double-Blind-Verfahren mit jeweils drei Gutachten und fĂŒhrte zu einer Annahmequote von 25%. Die WI2013 hat vom 27.02. - 01.03.2013 unter den Leitthemen Innovation, Integration und Individualisierung an der UniversitĂ€t Leipzig stattgefunden.:Track 1: Individualization and Consumerization Track 2: Integrated Systems in Manufacturing Industries Track 3: Integrated Systems in Service Industries Track 4: Innovations and Business Models Track 5: Information and Knowledge Managemen

    Visualizing Set Relations and Cardinalities Using Venn and Euler Diagrams

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    In medicine, genetics, criminology and various other areas, Venn and Euler diagrams are used to visualize data set relations and their cardinalities. The data sets are represented by closed curves and the data set relationships are depicted by the overlaps between these curves. Both the sets and their intersections are easily visible as the closed curves are preattentively processed and form common regions that have a strong perceptual grouping effect. Besides set relations such as intersection, containment and disjointness, the cardinality of the sets and their intersections can also be depicted in the same diagram (referred to as area-proportional) through the size of the curves and their overlaps. Size is a preattentive feature and so similarities, differences and trends are easily identified. Thus, such diagrams facilitate data analysis and reasoning about the sets. However, drawing these diagrams manually is difficult, often impossible, and current automatic drawing methods do not always produce appropriate diagrams. This dissertation presents novel automatic drawing methods for different types of Euler diagrams and a user study of how such diagrams can help probabilistic judgement. The main drawing algorithms are: eulerForce, which uses a force-directed approach to lay out Euler diagrams; eulerAPE, which draws area-proportional Venn diagrams with ellipses. The user study evaluated the effectiveness of area- proportional Euler diagrams, glyph representations, Euler diagrams with glyphs and text+visualization formats for Bayesian reasoning, and a method eulerGlyphs was devised to automatically and accurately draw the assessed visualizations for any Bayesian problem. Additionally, analytic algorithms that instantaneously compute the overlapping areas of three general intersecting ellipses are provided, together with an evaluation of the effectiveness of ellipses in drawing accurate area-proportional Venn diagrams for 3-set data and the characteristics of the data that can be depicted accurately with ellipses

    The Data Science Design Manual

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    EG-ICE 2021 Workshop on Intelligent Computing in Engineering

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    The 28th EG-ICE International Workshop 2021 brings together international experts working at the interface between advanced computing and modern engineering challenges. Many engineering tasks require open-world resolutions to support multi-actor collaboration, coping with approximate models, providing effective engineer-computer interaction, search in multi-dimensional solution spaces, accommodating uncertainty, including specialist domain knowledge, performing sensor-data interpretation and dealing with incomplete knowledge. While results from computer science provide much initial support for resolution, adaptation is unavoidable and most importantly, feedback from addressing engineering challenges drives fundamental computer-science research. Competence and knowledge transfer goes both ways

    Enabling the Development and Implementation of Digital Twins : Proceedings of the 20th International Conference on Construction Applications of Virtual Reality

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    Welcome to the 20th International Conference on Construction Applications of Virtual Reality (CONVR 2020). This year we are meeting on-line due to the current Coronavirus pandemic. The overarching theme for CONVR2020 is "Enabling the development and implementation of Digital Twins". CONVR is one of the world-leading conferences in the areas of virtual reality, augmented reality and building information modelling. Each year, more than 100 participants from all around the globe meet to discuss and exchange the latest developments and applications of virtual technologies in the architectural, engineering, construction and operation industry (AECO). The conference is also known for having a unique blend of participants from both academia and industry. This year, with all the difficulties of replicating a real face to face meetings, we are carefully planning the conference to ensure that all participants have a perfect experience. We have a group of leading keynote speakers from industry and academia who are covering up to date hot topics and are enthusiastic and keen to share their knowledge with you. CONVR participants are very loyal to the conference and have attended most of the editions over the last eighteen editions. This year we are welcoming numerous first timers and we aim to help them make the most of the conference by introducing them to other participants
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