Relevant bibliographies by topics / Visual modelling

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Visual modelling'

Author: Grafiati
Published: 4 June 2021
Last updated: 4 February 2022

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Journal articles on the topic "Visual modelling"

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Bezerra, Silvio, Armand Caron, and Yves Cherruault. "Visual modelling." International Journal of Bio-Medical Computing 32, no. 3-4 (May 1993): 181–95. http://dx.doi.org/10.1016/0020-7101(93)90013-v.

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Smith, V. L. "Visual Interactive Modelling." Journal of the Operational Research Society 37, no. 10 (October 1986): 1017. http://dx.doi.org/10.2307/2582292.

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Smith, V. L. "Visual Interactive Modelling." Journal of the Operational Research Society 37, no. 10 (October 1986): 1017–20. http://dx.doi.org/10.1057/jors.1986.173.

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Hurrion, R. D. "Visual interactive modelling." European Journal of Operational Research 23, no. 3 (March 1986): 281–87. http://dx.doi.org/10.1016/0377-2217(86)90293-6.

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Bell, Peter C. "Visual Interactive Modelling: Reply." Journal of the Operational Research Society 37, no. 10 (October 1986): 1020. http://dx.doi.org/10.2307/2582293.

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Semenenko, M. G. "Visual modelling electrochemical processes." Journal of Power Sources 191, no. 1 (June 2009): 91–96. http://dx.doi.org/10.1016/j.jpowsour.2008.10.128.

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Bell, Peter C. "Visual Interactive Modelling: Reply." Journal of the Operational Research Society 37, no. 10 (October 1986): 1020–21. http://dx.doi.org/10.1057/jors.1986.174.

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Hurrion, R. D. "Intelligent Visual Interactive Modelling." European Journal of Operational Research 54, no. 3 (October 1991): 349–56. http://dx.doi.org/10.1016/0377-2217(91)90110-h.

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Powers, M. K., and W. P. Fisher. "Advances in modelling visual symptoms and visual skills." Journal of Physics: Conference Series 1379 (November 2019): 012044. http://dx.doi.org/10.1088/1742-6596/1379/1/012044.

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Itti, Laurent, and Christof Koch. "Computational modelling of visual attention." Nature Reviews Neuroscience 2, no. 3 (March 2001): 194–203. http://dx.doi.org/10.1038/35058500.

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Dissertations / Theses on the topic "Visual modelling"

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Narbutas, Vilius. "Computational modelling of visual search." Thesis, University of Birmingham, 2018. http://etheses.bham.ac.uk//id/eprint/8772/.

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Visual search traditionally has two main competing theories of parallel and serial search and this architectural issue has not been solved to this day. The latest developments in the field have suggested a possibility that response time distributions may aid in differentiating the two competing theories. For this purpose we have used the best available serial model Competitive Guided Search and two biologically-plausible parallel models inspired by the theory of biased competition. The parallel models adopted a winner-take-all mechanism from Selective Attention for Identification Model as base model that was extended to form a novel model for explaining response time distributions. These models are analytically intractable, therefore we adopted a more accurate kernel density estimator for representing unknown probability density function. Introduced robustness properties to the fitness method and developed a more efficient algorithm for finding the parameter solutions. Then these methods were applied for comparison of the respective models and concluded that winner-takes-all model poorly generalises to response time distributions. The results were followed by introducing a novel Asymmetrical Dynamic Neural Network model that managed to explain distributional changes better than Competitive Guided Search model.
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Bühler, Frank Stefan. "Combining visual modelling with visual programming for CORBA component development." Thesis, De Montfort University, 2002. http://hdl.handle.net/2086/4068.

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Clarke, Alasdair Daniel Francis. "Modelling visual search for surface defects." Thesis, Heriot-Watt University, 2010. http://hdl.handle.net/10399/2351.

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Much work has been done on developing algorithms for automated surface defect detection. However, comparisons between these models and human perception are rarely carried out. This thesis aims to investigate how well human observers can nd defects in textured surfaces, over a wide range of task di culties. Stimuli for experiments will be generated using texture synthesis methods and human search strategies will be captured by use of an eye tracker. Two di erent modelling approaches will be explored. A computational LNL-based model will be developed and compared to human performance in terms of the number of xations required to find the target. Secondly, a stochastic simulation, based on empirical distributions of saccades, will be compared to human search strategies.
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Woodbury, Greg. "Modelling Emergent Properties of the Visual Cortex." University of Sydney. School of Mathematics and Statistics, 2003. http://hdl.handle.net/2123/695.

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Wu, Qi. "Modelling visual objects regardless of depictive style." Thesis, University of Bath, 2015. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.646137.

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Visual object classifcation and detection are major problems in contemporary com- puter vision. State-of-art algorithms allow thousands of visual objects to be learned and recognized, under a wide range of variations including lighting changes, occlusion and point of view etc. However, only a small fraction of the literature addresses the problem of variation in depictive styles (photographs, drawings, paintings etc.). This is a challenging gap but the ability to process images of all depictive styles and not just photographs has potential value across many applications. This thesis aims to narrow this gap. Our studies begin with primitive shapes. We provide experimental evidence that primitives shapes such as `triangle', `square', or `circle' can be found and used to fit regions in segmentations. These shapes corresponds to those used by artists as they draw. We then assume that an object class can be characterised by the qualitative shape of object parts and their structural arrangement. Hence, a novel hierarchical graph representation labeled with primitive shapes is proposed. The model is learnable and is able to classify over a broad range of depictive styles. However, as more depictive styles join, how to capture the wide variation in visual appearance exhibited by visual objects across them is still an open question. We believe that the use of a graph with multi-labels to represent visual words that exists in possibly discontinuous regions of a feature space can be helpful.
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Dziemianko, Michal. "Modelling eye movements and visual attention in synchronous visual and linguistic processing." Thesis, University of Edinburgh, 2013. http://hdl.handle.net/1842/9377.

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This thesis focuses on modelling visual attention in tasks in which vision interacts with language and other sources of contextual information. The work is based on insights provided by experimental studies in visual cognition and psycholinguistics, particularly cross-modal processing. We present a series of models of eye-movements in situated language comprehension capable of generating human-like scan-paths. Moreover we investigate the existence of high level structure of the scan-paths and applicability of tools used in Natural Language Processing in the analysis of this structure. We show that scan paths carry interesting information that is currently neglected in both experimental and modelling studies. This information, studied at a level beyond simple statistical measures such as proportion of looks, can be used to extract knowledge of more complicated patterns of behaviour, and to build models capable of simulating human behaviour in the presence of linguistic material. We also revisit classical model saliency and its extensions, in particular the Contextual Guidance Model of Torralba et al. (2006), and extend it with memory of target positions in visual search. We show that models of contextual guidance should contain components responsible for short term learning and memorisation. We also investigate the applicability of this type of model to prediction of human behaviour in tasks with incremental stimuli as in situated language comprehension. Finally we investigate the issue of objectness and object saliency, including their effects on eye-movements and human responses to experimental tasks. In a simple experiment we show that when using an object-based notion of saliency it is possible to predict fixation locations better than using pixel-based saliency as formulated by Itti et al. (1998). In addition we show that object based saliency fits into current theories such as cognitive relevance and can be used to build unified models of cross-referential visual and linguistic processing. This thesis forms a foundation towards a more detailed study of scan-paths within an object-based framework such as Cognitive Relevance Framework (Henderson et al., 2007, 2009) by providing models capable of explaining human behaviour, and the delivery of tools and methodologies to predict which objects would be attended to during synchronous visual and linguistic processing.
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Stewart, Finlay J. "Modelling visual-olfactory integration in free-flying Drosophila." Thesis, University of Edinburgh, 2010. http://hdl.handle.net/1842/3192.

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Flying fruit flies (Drosophila melanogaster) locate a concealed appetitive odour source most accurately in environments containing vertical visual contrasts (Frye et al, 2003). To investigate how visuomotor and olfactory responses interact to cause this phenomenon, I implement a tracking system capable of recording flies’ flight trajectories in three dimensions. I examine free-flight behaviour in three different visual environments, with and without food odour present. While odour localisation is facilitated by a random chequerboard pattern compared to a horizontally striped one, a single vertical landmark also facilitates odour localisation, but only if the odour source is situated close to the landmark. I implement a closed-loop systems-level model of visuomotor control consisting of three parallel subsystems which use wide-field optic flow cues to control flight behaviour. These are: an optomotor response to stabilise the model fly’s yaw orientation; a collision avoidance system to initiate rapid turns (saccades) away from looming obstacles; and a speed regulation system. This model reproduces in simulation many of the behaviours I observe in flies, including distinctive visually mediated ‘rebound’ turns following saccades. Using recordings of real odour plumes, I simulate the presence of an odorant in the arena, and investigate ways in which the olfactory input could modulate visuomotor control. In accordance with the principle of Occam’s razor, I identify the simplest mechanism of crossmodal integration that reproduces the observed pattern of visual effects on the odour localisation behaviour of flies. The resulting model uses the change in odour intensity to regulate the sensitivity of collision avoidance, resulting in visually mediated chemokinesis. Additionally, it is necessary to amplify the optomotor response whenever odour is present, increasing the model fly’s tendency to steer towards features of the visual environment. This could be viewed as a change in behavioural context brought about by the possibility of feeding. A novel heterogeneous visual environment is used to validate the model. While its predictions are largely borne out by experimental data, it fails to account for a pronounced odour-dependent attraction to regions of exclusively vertical contrast. I conclude that visual and olfactory responses of Drosophila are not independent, but that relatively simple interaction between these modalities can account for the observed visual dependence of odour source localisation.
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Lazarevic, N. "Background modelling and performance metrics for visual surveillance." Thesis, Kingston University, 2011. http://eprints.kingston.ac.uk/21831/.

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This work deals with the problems of performance evaluation and background modelling for the detection of moving objects in outdoor video surveillance datasets. Such datasets are typically affected by considerable background variations caused by global and partial illumination variations, gradual and sudden lighting condition changes, and non-stationary backgrounds. The large variation of backgrounds in typical outdoor video sequences requires highly adaptable and robust models able to represent the background at any time instance with sufficient accuracy. Furthermore, in real life applications it is often required to detect possible contaminations of the scene in real time or when new observations become available. A novel adaptive multi-modal algorithm for on-line background modelling is proposed. The proposed algorithm applies the principles of the Gaussian Mixture Model, previously used to model the grey-level (or colour) variations of individual pixels, to the modelling of illumination variations in image regions. The image observations are represented in the eigen-space, where the dimensionality of the data is significantly reduced using the method of the principal components analysis. The projections of image regions in the reduced eigen-space are clustered using K-means into clusters (or modes) of similar backgrounds and are modelled as multivariate Gaussian distributions. Such an approach allows the model to adapts to the changes in the dataset in a timely manner. This work proposed modifications to a previously published method for incremental update of the uni-modal eigne-models. The modifications are twofold. First, the incremental update is performed on the individual modes of the multi-modal model, and second, the mechanism for adding new dimensions is adapted to handle problems typical for outdoor video surveillance scenes with a wide range of illumination changes. Finally, a novel, objective, comparative, object-based methodology for performance evaluation of object detection is also developed. the proposed methodology is concerned with the evaluation of object detection in the context of the end-user defined quality of performance in complex video surveillance applications.
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Mineault, Patrick. "Parametric modelling of visual cortex at multiple scales." Thesis, McGill University, 2014. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=123020.

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The visual system is confronted with the daunting task of extracting behaviourally relevant visual information from noisy and ambiguous patterns of luminance falling on the retina. It solves this problem through a hierarchical architecture, in which the visual stimulus is iteratively re-encoded into ever more abstract representations which can drive behaviour. This thesis explores the question of how the computations performed by neurons in the visual hierarchy create behaviourally relevant representations. This question requires probing the visual system at multiple scales: computation is the role of single neurons and ensembles of neurons; representation is the function of multiple neurons within an area; hierarchical processing is an emergent process which involves multiple areas; and behaviour is defined at the full scale of the system, the psychophysical observer. To study visual processing at multiple scales, I propose to develop and apply parametric modelling methods in the context of systems identification. Systems identification seeks to establish the deterministic relationship between the input and the output of a system. Systems identification has proven particularly useful in the study of visual processing, where the input to the system can be easily controlled via sensory stimulation.Parametric modeling, built on the theory of Generalized Linear Models (GLMs), furnishes a common framework to analyze signals with different statistical properties which occur in the analysis of neural systems: spike trains, multi-unit activity, local field potentials and psychophysical decisions.In Chapter 2, I develop the parametric modeling framework which is used throughout this thesis in the context of psychophysical classification images. Results show that parametric modeling can infer a psychophysical observer's decision process with fewer trials than previously proposed methods. This allows the exploration of more complex, and potentially more informative, models of decision processes while retaining statistical tractability.In Chapter 3, I extend and apply this framework to the analysis of visual representations at the level of neuronal ensembles in area V4. The results show that it is possible to infer, from multi-unit activity and local field potential (LFP) signals, the representation of visual space at a fine-grained scale over several millimeters of cortex. Analysis of the estimated visual representations reveals that LFPs reflect both local sources of input and global biases in visual representation. These results resolve a persistent puzzle in the literature regarding the spatial reach of the local field potential.In Chapter 4, I extend and apply the same framework to the analysis of single-neuron responses in area MST of the dorsal visual stream. Results reveal that MST responses can be explained by the integration of their afferent input from area MT, provided that this integration is nonlinear. Estimated models reveal long suspected, but previously unconfirmed receptive field organization in MST neurons that allow them to respond to complex optic flow patterns. This receptive field organization and nonlinear integration allows more accurate estimation of the velocity of approaching objects from the population of MST neurons, thus revealing their possible functional role in vergence control and object motion estimation.Put together, these results demonstrate that with powerful statistical methods, it is possible to infer the nature of visual representations at multiple scales. In the discussion, I show how these results may be expanded to gain a better understanding of hierarchical visual processing at large.
Le système visuel est confronté à la difficile tâche d'extraire de l'information utile au comportement à partir de motifs complexes et ambigus détectés par la rétine. Il résout ce problème grâce à une architecture hiérarchique, dans laquelle le stimulus visuel est itérativement ré-encodé dans une représentation abstraite. Ce mémoire explore la question suivante : comment les computations performées par des neurones de la hiérarchie visuelle créent-elles des représentations permettant des comportements complexes?Cette question nécessite l'étude du système visuel à plusieurs échelles : la computation est le rôle de neurones et d'ensembles de neurones; la représentation est une fonction des neurones dans une aire du cerveau; la hiérarchie émerge de la communication entre de multiples aires du cerveau; et le comportement est défini à l'échelle du système visuel complet, l'observateur psychophysique.Afin d'étudier le système visuel à de multiple échelles, je développe et applique des méthodes de modélisation paramétrique dans le cadre de l'identification de système. Celle-ci a pour but d'établir la relation déterministe entre l'entrée d'un système et sa sortie. L'identification de système est particulièrement utile dans l'étude de la vision, où l'entrée du système peut être facilement contrôlée par stimulation sensorielle.La modélisation paramétrique, bâtie sur la théorie des modèles linéaires généralisés, offre un paradigme commun pour analyser des signaux ayant des propriétés statistiques disparates, souvent rencontrés dans l'étude du système nerveux: les potentiels d'action, l'activité d'ensemble de neurones, et les décisions psychophysiques.Dans le 2ème chapitre, je développe le paradigme d'analyse par modélisation paramétrique qui sera utilisé tout au long de ce mémoire dans le contexte des images de classification psychophysiques. Je démontre qu'il est possible d'inférer, grâce à ces méthodes, le processus décisionnel d'un observateur psychophysique avec moins de données que ce qui était précédemment possible. Cette avancée permet l'exploration de modèles psychophysiques plus complexes, et potentiellement plus informatifs sur le processus décisionnel de l'observateur.Dans le 3ème chapitre, j'applique ce paradigme à l'analyse des représentations visuelles au niveau d'ensembles neuronaux dans l'aire V4 du système visuel. Les résultats démontrent qu'il est possible, à partir de l'activité des champs de potentiel locaux (CPL), d'inférer la représentation corticale de l'espace visuel sur une échelle de plusieurs millimètres. Je démontre ainsi que les CPL reflètent à la fois des sources synaptiques locales et des biais globaux dans la représentation visuelle. Ces résultats résolvent une controverse dans la littérature concernant l'intégration spatiale des CPL.Dans le 4ème chapitre, j'applique ce même paradigme dans l'analyse de neurones dans l'aire MST du système visuel dorsal. Je révèle que les réponses dans MST peuvent être expliquées par l'intégration de sources afférentes provenant de l'aire MT; cependant, cette intégration se révèle nonlinéaire. Cette analyse révèle des propriétés longtemps soupçonnées mais jusqu'ici non confirmées des champs réceptifs des neurones dans MST; celles-ci leur permettent de communiquer de l'information sur les motifs de flux optique complexes. Cette organisation des champs réceptifs et l'intégration nonlinéaire permet d'extraire plus facilement la vélocité d'objets s'approchant de l'observateur à partir des réponses de la population de neurones dans MST, révélant un rôle insoupçonné de ces neurones dans l'estimation de la vélocité des objets.Pris ensemble, ces résultats démontrent qu'à l'aide de méthodes statistiques puissantes, il est possible d'inférer la nature des représentations visuelles à de multiples échelles. Dans la discussion, je démontre comment généraliser ces résultats afin d'obtenir une meilleure compréhension des computations hiérarchiques dans le système visuel.
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Jilani, Mohd Zairul Mazwan Bin. "Simultaneous modelling and clustering of visual field data." Thesis, Brunel University, 2017. http://bura.brunel.ac.uk/handle/2438/17227.

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In the health-informatics and bio-medical domains, clinicians produce an enormous amount of data which can be complex and high in dimensionality. This scenario includes visual field data, which are used for managing the second leading cause of blindness in the world: glaucoma. Visual field data are the most common type of data collected to diagnose glaucoma in patients, and usually the data consist of 54 or 76 variables (which are referred to as visual field locations). Due to the large number of variables, the six nerve fiber bundles (6NFB), which is a collection of visual field locations in groups, are the standard clusters used in visual field data to represent the physiological traits of the retina. However, with regard to classification accuracy of the data, this research proposes a technique to find other significant spatial clusters of visual field with higher classification accuracy than the 6NFB. This thesis presents a novel clustering technique, namely, Simultaneous Modelling and Clustering (SMC). SMC performs clustering on data based on classification accuracy using heuristic search techniques. The method searches a collection of significant clusters of visual field locations that indicate visual field loss progression. The aim of this research is two-fold. Firstly, SMC algorithms are developed and tested on data to investigate the effectiveness and efficiency of the method using optimisation and classification methods. Secondly, a significant clustering arrangement of visual field, which highly interrelated visual field locations to represent progression of visual field loss with high classification accuracy, is searched to complement the 6NFB in diagnosis of glaucoma. A new clustering arrangement of visual field locations can be used by medical practitioners together with the 6NFB to complement each other in diagnosis of glaucoma in patients. This research conducts extensive experiment work on both visual field and simulated data to evaluate the proposed method. The results obtained suggest the proposed method appears to be an effective and efficient method in clustering visual field data and 3 improving classification accuracy. The key contributions of this work are the novel model-based clustering of visual field data, effective and efficient algorithms for SMC, practical knowledge of visual field data in the diagnosis of glaucoma and the presentation a generic framework for modelling and clustering which is highly applicable to many other dataset/model combinations.
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Books on the topic "Visual modelling"

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Staples, Sandy. A review of visual inteactive modelling. London, Canada: Western Business School, University of Western Ontario, 1994.

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Bühler, Frank Stefan. Combining visual modelling with visual programming for CORBA component development. Leicester: De Montfort University, 2002.

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Bühler, Frank Stefan. Combining visual modelling with visual programming for CORBA component development. Leicester: De Montfort University, 2002.

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Bühler, Frank Stefan. Combining visual modelling with visual programming for CORBA component development. Leicester: De Montfort University, 2002.

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Coquillart, Sabine. From Object Modelling to Advanced Visual Communication. Berlin, Heidelberg: Springer Berlin Heidelberg, 1994.

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Coquillart, Sabine, Wolfgang Straßer, and Peter Stucki, eds. From Object Modelling to Advanced Visual Communication. Berlin, Heidelberg: Springer Berlin Heidelberg, 1994. http://dx.doi.org/10.1007/978-3-642-78291-6.

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Mitronikas, Pangiotis. A visual simulation environment for modelling of traffic scenes. Manchester: UMIST, 1996.

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Environment, Alberta Alberta. The Southern Rockies landscape planning pilot study: Visual resource modelling. [Edmonton]: Alberta Environment, Land and Forest Service, Integrated Resource Management Division, 2000.

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Angehrn, Albert A. "Visual interactive modelling and intelligent DSS: Putting theory into practice". Fontainbleau: INSEAD, 1986.

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Angehrn, Albert. Visual interactive modelling and intelligent DSS: Putting theory into practice. Fontainebleau, France: INSEAD, 1990.

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Book chapters on the topic "Visual modelling"

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Schauer, Reinhard, and Siegfried Schönberger. "Visual Object Modelling." In Database and Expert Systems Applications, 300–307. Vienna: Springer Vienna, 1992. http://dx.doi.org/10.1007/978-3-7091-7557-6_52.

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Gong, Shaogang, and Tao Xiang. "Modelling Gesture." In Visual Analysis of Behaviour, 95–131. London: Springer London, 2011. http://dx.doi.org/10.1007/978-0-85729-670-2_5.

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Gong, Shaogang, and Tao Xiang. "Towards Modelling Behaviour." In Visual Analysis of Behaviour, 39–65. London: Springer London, 2011. http://dx.doi.org/10.1007/978-0-85729-670-2_3.

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Hammel, Mark S., Przemyslaw Prusinkiewicz, and Brian Wyvill. "Modelling Compound Leaves Using Implicit Contours." In Visual Computing, 199–212. Tokyo: Springer Japan, 1992. http://dx.doi.org/10.1007/978-4-431-68204-2_13.

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Zboinska, Malgorzata A. "Boosting the Efficiency of Architectural Visual Scripts." In Modelling Behaviour, 479–90. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-24208-8_40.

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Hill, Geoff. "Visual and Mechanical Design." In Loudspeaker Modelling and Design, 139–41. New York, NY: Routledge, [2019]: Routledge, 2018. http://dx.doi.org/10.4324/9781351116428-32.

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Gong, Shaogang, and Tao Xiang. "Modelling Rare and Subtle Behaviours." In Visual Analysis of Behaviour, 251–66. London: Springer London, 2011. http://dx.doi.org/10.1007/978-0-85729-670-2_11.

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Marcelli, Angelo, Antonio Parziale, and Adolfo Santoro. "Modelling Visual Appearance of Handwriting." In Image Analysis and Processing – ICIAP 2013, 673–82. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-41184-7_68.

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Schelle, Alexander, and Peter Stütz. "Modelling Visual Communication with UAS." In Modelling and Simulation for Autonomous Systems, 81–98. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-47605-6_7.

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Hofmann, Heike. "Interactive Biplots for Visual Modelling." In COMPSTAT 2004 — Proceedings in Computational Statistics, 223–34. Heidelberg: Physica-Verlag HD, 2004. http://dx.doi.org/10.1007/978-3-7908-2656-2_18.

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Conference papers on the topic "Visual modelling"

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Terzopoulos, Demetri. "Visual Modelling." In British Machine Vision Conference 1991. Springer-Verlag London Limited, 1991. http://dx.doi.org/10.5244/c.5.2.

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Gil, Joseph, John Howse, and Stuart Kent. "Advanced visual modelling." In the 24th international conference. New York, New York, USA: ACM Press, 2002. http://dx.doi.org/10.1145/581339.581451.

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Sun, L., S. Uchikado, M. Kawata, and K. Tanaka. "On Analysis of Vanishing Point Visual Control System for Image-based Visual Servoing." In Modelling and Simulation. Calgary,AB,Canada: ACTAPRESS, 2010. http://dx.doi.org/10.2316/p.2010.697-028.

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Chatzilari, Elisavet, Spiros Nikolopoulos, Yiannis Kompatsiaris, and Josef Kittler. "Towards modelling visual ambiguity for visual object detection." In the 14th International Conference. New York, New York, USA: ACM Press, 2014. http://dx.doi.org/10.1145/2637748.2638431.

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Poomarin, Warin, Kamol Chuengsatiansup, and Ratchatin Chancharoen. "Visual Positioning of a Delta Robot." In Modelling, Identification and Control. Calgary,AB,Canada: ACTAPRESS, 2013. http://dx.doi.org/10.2316/p.2013.799-109.

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Fu, Qinbing, and Shigang Yue. "Modelling LGMD2 visual neuron system." In 2015 IEEE 25th International Workshop on Machine Learning for Signal Processing (MLSP). IEEE, 2015. http://dx.doi.org/10.1109/mlsp.2015.7324313.

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Blažič, S., G. Mušič, D. Matko, G. Klančar, T. Rodič, and K. Oštir. "Image based Visual Servoing of a Remote Sensing Satellite." In Modelling and Simulation. Calgary,AB,Canada: ACTAPRESS, 2010. http://dx.doi.org/10.2316/p.2010.697-032.

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Ko, M. S., S. C. Park, and G. N. Wang. "Visual Validation Of PLC Programs." In 22nd Conference on Modelling and Simulation. ECMS, 2008. http://dx.doi.org/10.7148/2008-0410.

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Lee, Gil-Je, Dae-Soo Kim, and Kee-Young Yoo. "A Triple Access Control System based on Visual Secret Sharing." In Modelling and Simulation. Calgary,AB,Canada: ACTAPRESS, 2013. http://dx.doi.org/10.2316/p.2013.802-072.

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Buono, Paolo, and Angela Locoro. "Modelling Data Visualization Interactions." In AVI '20: International Conference on Advanced Visual Interfaces. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3399715.3399903.

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Reports on the topic "Visual modelling"

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Mahat, Marian, and Wesley Imms. A Day in the Life of a Student: Facilitator Guide. University of Melbourne, 2020. http://dx.doi.org/10.46580/124325.

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Abstract:
A Day in the Life of a Student workshop is a design thinking workshop developed by DLR Group (an integrated design firm) and adapted by the Innovative Learning Environment and Teacher Change project at the University of Melbourne, Australia. The activities involve educators mapping out how one student spends his/her day in school and building a model of the learning environment based on this one student. With an emphasis on the visual learning that comes from modelling experiences, this workshop helps participants develop student-improvement focused practices in innovative learning environments.
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