Gotowe bibliografie tematyczne / Visual representation

Gotowa bibliografia na temat „Visual representation”

Autor: Grafiati
Data publikacji: 4 czerwca 2021
Data aktualizacji: 10 marca 2023

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Artykuły w czasopismach na temat "Visual representation"

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Lee, Jungmin, i Wongyoung Lee. "Aspects of A Study on the Multi Presentational Metaphor Education Using Online Telestration". Korean Society of Culture and Convergence 44, nr 9 (30.09.2022): 163–73. http://dx.doi.org/10.33645/cnc.2022.9.44.9.163.

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This study is an attempt to propose a multiple representational metaphor education model that combines linguistic representation and visual representation using online telestration. The advent of the media and online era has incorporated not only the understanding of linguistic representation l but also the understanding of visual representation into an important phase of cognitive behavior and requires the implementation of online learning. In such an era's needs, it can be said that teaching-learning makes metaphors be used as a tool for thinking and cognition in an online environment, learning leads learners to a new horizon of perception by combining linguistic representation and visual representation. The multiple representational metaphor education model using online telestration will have a two-way dynamic interaction in an online environment, and it will be possible to improve learning capabilities by expressing various representations. Multiple representational metaphor education using online telestration will allow us to consider new perspectives and various possibilities of expression to interpret the world by converging and rephrasing verbal and visual representations using media in an online environment.
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Ruliani, Iva Desi, Nizaruddin Nizaruddin i Yanuar Hery Murtianto. "Profile Analysis of Mathematical Problem Solving Abilities with Krulik & Rudnick Stages Judging from Medium Visual Representation". JIPM (Jurnal Ilmiah Pendidikan Matematika) 7, nr 1 (7.09.2018): 22. http://dx.doi.org/10.25273/jipm.v7i1.2123.

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The ability to solve mathematical problems is very important in learning math and everyday life. According to Krulik & Rudnick there are 5 stages of problem solving that is Read, Explore, Select A Strategy, Solve And Look Back. Mathematical problems require multiple representational skills to communicate problems, one of which is visual representation. Trigonometry is one of the materials that uses visual representation. This research is a qualitative descriptive research that aims to describe the ability of problem solving mathematics with Krulik & Rudnick stages in terms of visual representation. The study was conducted in MAN 2 Brebes. Determination of Subjects in this study using Purposive Sampling. Research instruments used to obtain the required data are visual representation and problem-solving tests, and interview guidelines. The data obtained were analyzed based on the Krulik & Rudnick problem solving indicator. Subjects in this study were subjects with moderate visual representation. Based on the results, problem solving ability of the subject is not fully fulfilled. Subjects with visual representations are able to do problem solving well that is solving the problem through a concept that is understood without visualization of the image. Subjects with visual representations are having a schematic visual representation type.
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Stanczak, Gregory C. "Visual Representation". American Behavioral Scientist 47, nr 12 (sierpień 2004): 1471–76. http://dx.doi.org/10.1177/0002764204266234.

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Dilworth, John. "Varieties of Visual Representation". Canadian Journal of Philosophy 32, nr 2 (czerwiec 2002): 183–205. http://dx.doi.org/10.1080/00455091.2002.10716517.

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By a ‘visual representation’ I mean roughly an item that is both visible itself, and which purports to represent some actual subject (that in paradigm cases is also visible), in such a way that the representing item is in some way similar to, or recognizable as, the purported actual subject; and which item has a representational content or subject matter that may or may not accurately characterize any actual subject. Pictorial representation is one species of visual representation. However, one of my main concerns in this paper will be to argue that there are no less than three additional varieties or species of visual representation, none of which are currently adequately recognized, and which together comprise a category of visual representation distinct from that of pictorial representation.
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ROLAND, P., i B. GULYAS. "Visual imagery and visual representation". Trends in Neurosciences 17, nr 7 (1994): 281–87. http://dx.doi.org/10.1016/0166-2236(94)90057-4.

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Susanti, Susanti, Zainal Abidin i Rina Mauliza. "ANALISIS KEMAMPUAN REPRESENTASI MATEMATIS SISWA MELALUI PENERAPAN STRATEGI SCAFFOLDING". Jurnal Ilmiah Pendidikan Matematika Al Qalasadi 5, nr 1 (9.07.2021): 99–116. http://dx.doi.org/10.32505/qalasadi.v5i1.2912.

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This descriptive qualitative research aims to describe the mathematical representation abilities of students through the application of the scaffolding strategy. The subjects of this study were 2 students with low representation abilities and 2 students with moderate representation abilities in class VIII-4 of SMP Negeri 6 Banda Aceh. The data was collected by means of a mathematical representation ability test sheet, interviews, and a recording device. Then data analysis by reducing data, presenting data, triangulating time, and drawing conclusions. The results showed that subjects with low representation skills tended to perform visual representations, but after scaffolding they were able to use visual representations independently and verbal representations by checking several times. Meanwhile, subjects with moderate representation ability tend to perform visual and verbal representations with multiple checks and symbolic representations with several interventions, after scaffolding they are able to use visual and verbal representations independently, even though symbolic representations still require several interventions. This shows that the students' representation ability gets better after being given a scaffolding strategy.
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Chen, Deng-Jyi, Wu-Chi Chen i Krishna M. Kavi. "Visual requirement representation". Journal of Systems and Software 61, nr 2 (marzec 2002): 129–43. http://dx.doi.org/10.1016/s0164-1212(01)00108-x.

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Suárez, Luis Alfonso de la Fuente. "TOWARDS EXPERIENTIAL REPRESENTATION IN ARCHITECTURE". Journal of Architecture and Urbanism 40, nr 1 (6.04.2016): 47–58. http://dx.doi.org/10.3846/20297955.2016.1163243.

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Planning and predicting the experiences that buildings will produce is an essential part of architectural design. The importance of representation lies in its ability to communicate experiences before a building is materialized. This article will treat the topic of representation of architecture works without putting aside our direct experience with edifices. By understanding the perceptual, associative and interactive phenomena that arise from the human encounter with buildings, it becomes possible to comprehend the representation of these phenomena through pictorial means. The first objective of this theoretical article is to define the inherent and unavoidable factors that are present in the creation and interpretation of all architectural representations, regardless of the technical means used. Any representation conveys two processes: the representation of experience (a creative process), and the experience of representation (an interpretive process). Furthermore, there exist two layers in any representation: the what (the architectural object) and the how (the representational medium). The second objective is to suggest alternatives to visual realism, in order to create representations that embody the particular phenomena that an architectural work will be able to produce. On the one hand, representations that pretend to copy reality produce in the observers detailed visual experiences; on the other hand, certain representations reflect the experiences themselves after they have been produced; they represent buildings as they are transformed by experience. This article focuses on those representations that are not only the reflection of an object, but also the reflection of our way of experiencing it.
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Amaliyah AR, Rezki, i Nurfadilah Mahmud. "Analisis Kemampuan Representasi Matematis dalam Pemecahan Masalah Geometri serta Faktor-Faktor yang Mempengaruhinya". Jurnal Review Pembelajaran Matematika 3, nr 2 (15.12.2018): 146–60. http://dx.doi.org/10.15642/jrpm.2018.3.2.146-160.

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This is qualitative research with a descriptive-explorative approach that aims to determine students' mathematical representation skills in solving Geometry problems. The population is all students in the mathematics education department who study Basic Geometry. The main subject was chosen by stratified technique and purposive sampling. The instruments are placement tests, diagnostic tests, and guided interviews. Data collection uses a triangulation method that aims to examine legitimate data. The results showed that 1) subjects with high skills always present visual representations and mathematical expressions, 2) subjects with intermediate skills present visual representations and mathematical expressions, and verbal but less representative representations, 3) subjects with low skills don’t present visual representations and mathematical expressions and verbal representations of problem-solving steps; and 4) there are several factors that influence the ability of mathematical representation to solve geometric problems, among others, subjects are less able to present problems in geometric patterns, because the subject does not understand the problem.
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Vrotsou, Katerina, Camilla Forsell i Matthew Cooper. "2D and 3D Representations for Feature Recognition in Time Geographical Diary Data". Information Visualization 9, nr 4 (3.12.2009): 263–76. http://dx.doi.org/10.1057/ivs.2009.30.

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Time geographical representations are becoming a common approach to analysing spatio-temporal data. Such representations appear intuitive in the process of identifying patterns and features as paths of populations form tracks through the 3D space, which can be seen converging and diverging over time. In this article, we compare 2D and 3D representations within a time geographical visual analysis tool for activity diary data. We identify a representative task and evaluate task performance between the two representations. The results show that the 3D representation has benefits over the 2D representation for feature identification but also indicate that these benefits can be lost if the 3D representation is not carefully constructed to help the user to see them.
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Rozprawy doktorskie na temat "Visual representation"

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Pihlström, Max. "Visual representation by triangulation". Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-264109.

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n this thesis the triangulation is treated as a general-purpose visual representation by investigation of various domain-specific methods such as triangulation interpolation, mesh flows, vertex neighborhood feature measures and re-triangulation for spatial transformations. Suggested new methods include an effective cost for image interpolation based on work by Sederberg et al. and a ridge-edge measure related to the Harris edge detector.
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Mazein, Alexander. "Visual representation of cellular networks". Thesis, University of Edinburgh, 2011. http://hdl.handle.net/1842/5295.

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Development of advanced techniques for biological network visualisation is crucial for successful progress in the areas of systems-level biology and data-intensive bioinformatics. However, current techniques for biological network visualisation fall short of expectations for representing extensive biological networks. In order to provide really useful network visualisation tools, new approaches have to be proposed and applied alongside with those most powerful features of current visualisation systems. The resulting representation techniques have to be tested by applying to large-scale examples that would include metabolic, signaling and gene expression events. User survey should also be carried out to further prove the advantages of the new techniques. The present thesis describes an attempt to achieve the above objectives, by performing the following steps: 1) existing approaches in the area of network representation were analyzed and their shortcomings and advantages were defined; 2) new notation has been developed, in which, the defined best features of the existing systems were integrated with newly introduced potent features such as compact visualization, ‘functional gate’ and ‘identity gate’, 4) new framework was developed that allows managing large-scale networks that are represented on different levels of details and different levels of constrains, while keeping each diagram semantically unambiguous, 5) extensive examples, including genome-scaled human metabolic network and TNF-alpha receptor signalling network, were used to prove that the designed notation and the framework can be applied efficiently, and, finally, 6) a notation survey has been carried out to validate the advantages of the newly developed notation over the existing ones.
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Dakin, S. C. "The visual representation of texture". Thesis, University of Stirling, 1994. http://hdl.handle.net/1893/3503.

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This research is concerned with texture: a source of visual information, that has motivated a huge amount of psychophysical and computational research. This thesis questions how useful the accepted view of texture perception is. From a theoretical point of view, work to date has largely avoided two critical aspects of a computational theory of texture perception. Firstly, what is texture? Secondly, what is an appropriate representation for texture? This thesis argues that a task dependent definition of texture is necessary, and proposes a multi-local, statistical scheme for representing texture orientation. Human performance on a series of psychophysical orientation discrimination tasks are compared to specific predictions from the scheme. The first set of experiments investigate observers' ability to directly derive statistical estimates from texture. An analogy is reported between the way texture statistics are derived, and the visual processing of spatio-luminance features. The second set of experiments are concerned with the way texture elements are extracted from images (an example of the generic grouping problem in vision). The use of highly constrained experimental tasks, typically texture orientation discriminations, allows for the formulation of simple statistical criteria for setting critical parameters of the model (such as the spatial scale of analysis). It is shown that schemes based on isotropic filtering and symbolic matching do not suffice for performing this grouping, but that the scheme proposed, base on oriented mechanisms, does. Taken together these results suggest a view of visual texture processing, not as a disparate collection of processes, but as a general strategy for deriving statistical representations of images common to a range of visual tasks.
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Found, Andrew Paul. "Visual search : process and representation". Thesis, Birkbeck (University of London), 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.265002.

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Wang, Zhaoqing. "Self-supervised Visual Representation Learning". Thesis, The University of Sydney, 2022. https://hdl.handle.net/2123/29595.

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In general, large-scale annotated data are essential to training deep neural networks in order to achieve better performance in visual feature learning for various computer vision applications. Unfortunately, the amount of annotations is challenging to obtain, requiring a high cost of money and human resources. The dependence on large-scale annotated data has become a crucial bottleneck in developing an advanced intelligence perception system. Self-supervised visual representation learning, a subset of unsupervised learning, has gained popularity because of its ability to avoid the high cost of annotated data. A series of methods designed various pretext tasks to explore the general representations from unlabeled data and use these general representations for different downstream tasks. Although previous methods achieved great success, the label noise problem exists in these pretext tasks due to the lack of human-annotation supervision, which causes harmful effects on the transfer performance. This thesis discusses two types of the noise problem in self-supervised learning and designs the corresponding methods to alleviate the negative effects and explore the transferable representations. Firstly, in pixel-level self-supervised learning, the pixel-level correspondences are easily noisy because of complicated context relationships (e.g., misleading pixels in the background). Secondly, two views of the same image share the foreground object and some background information. As optimizing the pretext task (e.g., contrastive learning), the model is easily to capture the foreground object and noisy background information, simultaneously. Such background information can be harmful to the transfer performance on downstream tasks, including image classification, object detection, and instance segmentation. To address the above mentioned issues, our core idea is to leverage the data regularities and prior knowledge. Experimental results demonstrate that the proposed methods effectively alleviate the negative effects of label noise in self-supervised learning and surpass a series of previous methods.
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Sandy, Shiva S. (Shiva Sean) 1976. "Visual discussions : a visual representation of threaded discussion groups". Thesis, Massachusetts Institute of Technology, 1998. http://hdl.handle.net/1721.1/46256.

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Thesis (S.B. and M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1998.
Includes bibliographical references (leaves 39-41).
This is an M.Eng thesis, based on software development work done in collaboration with Lotus Development Corp. In this project we are creating a visual overview of ongoing threads of a discussion database. This will allow users to quickly focus their attention to relevant areas of areas in a large information space.
by Shiva S. Sandy.
S.B.and M.Eng.
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Ellis, R. "Levels of representation for visual objects". Thesis, University of Oxford, 1985. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.355746.

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Welchman, Andrew Edward. "Human visual representation and filling-in". Thesis, University of Newcastle Upon Tyne, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.327185.

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Bantinaki, Katerina. "The visual character of pictorial representation". Thesis, King's College London (University of London), 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.429510.

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Rakover, Nicolas. "A uniform representation for visual concepts". Thesis, Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/105965.

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Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2016.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 54-55).
We present a method for learning visually-grounded word meanings, given as input a set of videos paired with natural-language sentences describing them. Our method uses a uniform feature representation for all words and word types rather than relying on handcrafted features specific to each word. We learn words in a weakly-supervised manner, with no need for annotated bounding boxes around objects of interest. We encode words as Hidden Markov models such that word models can be composed according to a sentence's semantic structure to efficiently recognize events in videos. We use a discriminative variant of Baum-Welch to learn the parameters for our word models, and demonstrate that our approach is able to learn words capturing appearance, spatial relations, and temporal dynamics.
by Nicolas Rakover.
M. Eng.
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Książki na temat "Visual representation"

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Sociology and visual representation. London: Routledge, 1994.

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Atzori, Luigi, Daniel D. Giusto, Riccardo Leonardi i Fernando Pereira, red. Visual Content Processing and Representation. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11738695.

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García, Narciso, Luis Salgado i José M. Martínez, red. Visual Content Processing and Representation. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/b13938.

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Marlis, Schweitzer, i University of Toronto at Mississauga., red. VCC 306 : Gender & visual representation. Mississauga: University of Toronto at Mississauga, 2004.

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Timothy, Druckrey, red. Electronic culture: Technology and visual representation. New York: Aperture, 1996.

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Colored pictures: Race and visual representation. Chapel Hill: University of North Carolina Press, 2003.

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Farber, Leora. Imaging ourselves: Visual identities in representation. Johannesburg: University of Johannesburg, Faculty of Art Design and Architecture, 2009.

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Stephenson, David Hanford. On the visual representation of music. Ann Arbor, Mich: U.M.I., 1989.

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Seeing objects: The structure of visual representation. Paderborn: mentis, 2010.

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Tomaselli, Keyan G. Appropriating images: The semiotics of visual representation. Højbjerg, Denmark: Intervention Press, 1996.

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Części książek na temat "Visual representation"

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Haindl, Michal, i Jiří Filip. "Representation". W Visual Texture, 9–22. London: Springer London, 2013. http://dx.doi.org/10.1007/978-1-4471-4902-6_2.

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Ioannidis, Yannis. "Visual Representation". W Encyclopedia of Database Systems, 1–6. New York, NY: Springer New York, 2016. http://dx.doi.org/10.1007/978-1-4899-7993-3_449-2.

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Ioannidis, Yannis. "Visual Representation". W Encyclopedia of Database Systems, 3405–10. Boston, MA: Springer US, 2009. http://dx.doi.org/10.1007/978-0-387-39940-9_449.

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Ioannidis, Yannis. "Visual Representation". W Encyclopedia of Database Systems, 4542–48. New York, NY: Springer New York, 2018. http://dx.doi.org/10.1007/978-1-4614-8265-9_449.

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Chong, Sang Chul, i Yihwa Baek. "Ensemble representation". W Visual Memory, 105–18. New York: Routledge, 2022. http://dx.doi.org/10.4324/9781003158134-7.

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Lewis, Clayton. "Non-visual Visual Programming I: Dataflow". W Representation, Inclusion, and Innovation, 43–47. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-031-02221-0_5.

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Sanniti di Baja, Gabriella. "Visual Form Representation". W Human and Machine Vision, 115–29. Boston, MA: Springer US, 1994. http://dx.doi.org/10.1007/978-1-4899-1004-2_8.

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Wu, Qi, Peng Wang, Xin Wang, Xiaodong He i Wenwu Zhu. "Video Representation Learning". W Visual Question Answering, 111–17. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-0964-1_7.

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Arya, Rina. "Abjection in the Visual Arts". W Abjection and Representation, 82–117. London: Palgrave Macmillan UK, 2014. http://dx.doi.org/10.1057/9780230389342_5.

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Möller, Frank. "Impressions: Stretching the Limits of Representation". W Visual Peace, 3–23. London: Palgrave Macmillan UK, 2013. http://dx.doi.org/10.1057/9781137020406_1.

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Streszczenia konferencji na temat "Visual representation"

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Goldberg, Joseph H., i Jonathan I. Helfman. "Visual scanpath representation". W the 2010 Symposium. New York, New York, USA: ACM Press, 2010. http://dx.doi.org/10.1145/1743666.1743717.

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Jaybhay, Sheetal, Dhruvi Jain, Siddhi Bhagat, Priya Chaudhari i Vanessa Dbritto. "‘Envision’: Visual Representation System". W 2020 3rd International Conference on Communication System, Computing and IT Applications (CSCITA). IEEE, 2020. http://dx.doi.org/10.1109/cscita47329.2020.9137794.

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Jobson, Daniel J., Zia-ur Rahman i Glenn A. Woodell. "Statistics of visual representation". W AeroSense 2002, redaktorzy Zia-ur Rahman, Robert A. Schowengerdt i Stephen E. Reichenbach. SPIE, 2002. http://dx.doi.org/10.1117/12.477589.

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Mopuri, Konda Reddy, i R. Venkatesh Babu. "Towards semantic visual representation". W the Tenth Indian Conference. New York, New York, USA: ACM Press, 2016. http://dx.doi.org/10.1145/3009977.3010010.

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Xie, Ruobing, Zhiyuan Liu, Huanbo Luan i Maosong Sun. "Image-embodied Knowledge Representation Learning". W Twenty-Sixth International Joint Conference on Artificial Intelligence. California: International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/438.

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Entity images could provide significant visual information for knowledge representation learning. Most conventional methods learn knowledge representations merely from structured triples, ignoring rich visual information extracted from entity images. In this paper, we propose a novel Image-embodied Knowledge Representation Learning model (IKRL), where knowledge representations are learned with both triple facts and images. More specifically, we first construct representations for all images of an entity with a neural image encoder. These image representations are then integrated into an aggregated image-based representation via an attention-based method. We evaluate our IKRL models on knowledge graph completion and triple classification. Experimental results demonstrate that our models outperform all baselines on both tasks, which indicates the significance of visual information for knowledge representations and the capability of our models in learning knowledge representations with images.
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Stanhill, David, i Yehoshua Y. Zeevi. "Finding the optimal wavelet functions for image representation". W Visual Communications '93, redaktorzy Barry G. Haskell i Hsueh-Ming Hang. SPIE, 1993. http://dx.doi.org/10.1117/12.157929.

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Zibulski, Meir, i Yehoshua Y. Zeevi. "Matrix algebra approach to Gabor-type image representation". W Visual Communications '93, redaktorzy Barry G. Haskell i Hsueh-Ming Hang. SPIE, 1993. http://dx.doi.org/10.1117/12.157934.

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Westmoreland, Sophoria, Ashley Grenier i Linda C. Schmidt. "Analysis of Capstone Design Reports: Visual Representations". W ASME 2008 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2008. http://dx.doi.org/10.1115/detc2008-49378.

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Engineers require effective written communication skills, including the appropriate presentation of mechanical design information in visual format. A study of 48 Capstone Design Reports submitted over a period 5 semesters gives insight into the choices students make when selecting visual representations for describing designs. Student choices reflect assignment requirements, student preference, student skill level, and perceived appropriateness of representation type. This study presents observations on the use of visuals in a set of Capstone Design Reports with particular emphasis on sketches.
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Shen, William, Danfei Xu, Yuke Zhu, Li Fei-Fei, Leonidas Guibas i Silvio Savarese. "Situational Fusion of Visual Representation for Visual Navigation". W 2019 IEEE/CVF International Conference on Computer Vision (ICCV). IEEE, 2019. http://dx.doi.org/10.1109/iccv.2019.00297.

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Yan-Tao Zheng, Ming Zhao, Shi-Yong Neo, Tat-Seng Chua i Qi Tian. "Visual Synset: Towards a higher-level visual representation". W 2008 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2008. http://dx.doi.org/10.1109/cvpr.2008.4587611.

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Raporty organizacyjne na temat "Visual representation"

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Schunn, Christian D., Lelyn D. Saner, Susan K. Kirschenbaum, J. G. Trafton i Eliza B. Littleton. Complex Visual Data Analysis, Uncertainty, and Representation. Fort Belvoir, VA: Defense Technical Information Center, styczeń 2007. http://dx.doi.org/10.21236/ada479656.

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Schacter, Daniel L., i Lynn A. Cooper. Forms of Memory for Representation of Visual Objects. Fort Belvoir, VA: Defense Technical Information Center, luty 1992. http://dx.doi.org/10.21236/ada250056.

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Schacter, Daniel L. Forms Of Memory For Representation Of Visual Objects. Fort Belvoir, VA: Defense Technical Information Center, luty 1991. http://dx.doi.org/10.21236/ada264826.

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Schacter, Daniel L., i Lynn A. Cooper. Forms of Memory for Representation of Visual Objects. Fort Belvoir, VA: Defense Technical Information Center, kwiecień 1991. http://dx.doi.org/10.21236/ada267634.

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Sternberg, Saul. The Dynamics of Visual Representation, Attention, Encoding, and Retrieval Processes. Fort Belvoir, VA: Defense Technical Information Center, październik 1991. http://dx.doi.org/10.21236/ada243031.

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Soatto, Stefano. Visual Information Theory and Visual Representation for Achieving Provable Bounds in Vision-Based Control and Decision. Fort Belvoir, VA: Defense Technical Information Center, lipiec 2014. http://dx.doi.org/10.21236/ada611903.

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McGaughey, R. J., i R. H. Twito. VISUAL and SLOPE: perspective and quantitative representation of digital terrain models. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station, 1988. http://dx.doi.org/10.2737/pnw-gtr-214.

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Schunn, Christian D., Lelyn D. Saner, J. G. Trafton, Susan B. Trickett, Susan K. Kirschenbaum, Michael Knepp i Melanie Shoup. The Evolution of Spatial Representation During Complex Visual Data Analysis: Knowing When and How to be Exact. Fort Belvoir, VA: Defense Technical Information Center, wrzesień 2005. http://dx.doi.org/10.21236/ada445030.

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Kud, A. A. Figures and Tables. Reprinted from “Comprehensive сlassification of virtual assets”, A. A. Kud, 2021, International Journal of Education and Science, 4(1), 52–75. KRPOCH, 2021. http://dx.doi.org/10.26697/reprint.ijes.2021.1.6.a.kud.

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Figure. Distributed Ledger Token Accounting System. Figure. Subjects of Social Relations Based on the Decentralized Information Platform. Figure. Derivativeness of a Digital Asset. Figure. Semantic Features of the Concept of a “Digital Asset” in Economic and Legal Aspects. Figure. Derivativeness of Polyassets and Monoassets. Figure. Types of Tokenized Assets Derived from Property. Figure. Visual Representation of the Methods of Financial and Management Accounting of Property Using Various Types of Tokenized Assets. Figure. Visual Representation of the Classification of Virtual Assets Based on the Complexity of Their Nature. Table. Comparison of Properties of Various Types of Virtual Assets of the Distributed Ledger Derivative of the Original Asset. Table. Main Properties and Parameters of Types of Tokenized Assets. Table. Classification of Virtual Assets as Tools for Implementing the Methods of Financial and Management Accounting of Property.
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Yan, Yujie, i Jerome F. Hajjar. Automated Damage Assessment and Structural Modeling of Bridges with Visual Sensing Technology. Northeastern University, maj 2021. http://dx.doi.org/10.17760/d20410114.

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Recent advances in visual sensing technology have gained much attention in the field of bridge inspection and management. Coupled with advanced robotic systems, state-of-the-art visual sensors can be used to obtain accurate documentation of bridges without the need for any special equipment or traffic closure. The captured visual sensor data can be post-processed to gather meaningful information for the bridge structures and hence to support bridge inspection and management. However, state-of-the-practice data postprocessing approaches require substantial manual operations, which can be time-consuming and expensive. The main objective of this study is to develop methods and algorithms to automate the post-processing of the visual sensor data towards the extraction of three main categories of information: 1) object information such as object identity, shapes, and spatial relationships - a novel heuristic-based method is proposed to automate the detection and recognition of main structural elements of steel girder bridges in both terrestrial and unmanned aerial vehicle (UAV)-based laser scanning data. Domain knowledge on the geometric and topological constraints of the structural elements is modeled and utilized as heuristics to guide the search as well as to reject erroneous detection results. 2) structural damage information, such as damage locations and quantities - to support the assessment of damage associated with small deformations, an advanced crack assessment method is proposed to enable automated detection and quantification of concrete cracks in critical structural elements based on UAV-based visual sensor data. In terms of damage associated with large deformations, based on the surface normal-based method proposed in Guldur et al. (2014), a new algorithm is developed to enhance the robustness of damage assessment for structural elements with curved surfaces. 3) three-dimensional volumetric models - the object information extracted from the laser scanning data is exploited to create a complete geometric representation for each structural element. In addition, mesh generation algorithms are developed to automatically convert the geometric representations into conformal all-hexahedron finite element meshes, which can be finally assembled to create a finite element model of the entire bridge. To validate the effectiveness of the developed methods and algorithms, several field data collections have been conducted to collect both the visual sensor data and the physical measurements from experimental specimens and in-service bridges. The data were collected using both terrestrial laser scanners combined with images, and laser scanners and cameras mounted to unmanned aerial vehicles.
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