Academic literature on the topic 'Visual and performative learning'
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Journal articles on the topic "Visual and performative learning"
Sastre, Cibele. "Learning/teaching, creating and performing through LBMS." Journal of Dance & Somatic Practices 12, no. 1 (August 1, 2020): 95–106. http://dx.doi.org/10.1386/jdsp_00015_1.
Full textGrushka, Kathryn. "Conceptualising Visual Learning as an Embodied and Performative Pedagogy for all Classrooms." Encounters in Theory and History of Education 11 (November 28, 2010): 13–23. http://dx.doi.org/10.24908/eoe-ese-rse.v11i0.3167.
Full textOwen, Craig, and Sarah Riley. "Teaching Visual Methods Using Performative Storytelling, Reflective Practice and Learning through Doing." Psychology Learning & Teaching 11, no. 1 (January 1, 2012): 60–65. http://dx.doi.org/10.2304/plat.2012.11.1.60.
Full textGrushka, Kathryn. "Meaning and identities: a visual performative pedagogy for socio‐cultural learning." Curriculum Journal 20, no. 3 (September 2009): 237–51. http://dx.doi.org/10.1080/09585170903195860.
Full textDolan, Jill. "Geographies of Learning: Theatre Studies, Performance, and the "Performative"." Theatre Journal 45, no. 4 (December 1993): 417. http://dx.doi.org/10.2307/3209014.
Full textClifton, Shirley, and Kathryn Grushka. "Rendering Artful and Empathic Arts-Based Performance as Action." LEARNing Landscapes 15, no. 1 (June 23, 2022): 89–107. http://dx.doi.org/10.36510/learnland.v15i1.1066.
Full textSebiane Serrano, Leonardo José. "Mestizo Corporalities: Tropical/vibrant Latin American bodies." Journal of Dance & Somatic Practices 12, no. 1 (August 1, 2020): 107–25. http://dx.doi.org/10.1386/jdsp_00016_1.
Full textHuebner, Emma June. "TikTok and museum education: A visual content analysis." International Journal of Education Through Art 18, no. 2 (June 1, 2022): 209–25. http://dx.doi.org/10.1386/eta_00095_1.
Full textTrezise, Bryoni. "Performative pedagogies: feeling the experience of being (the) social in twenty-first century learning." Research in Drama Education: The Journal of Applied Theatre and Performance 25, no. 3 (July 2, 2020): 465–79. http://dx.doi.org/10.1080/13569783.2020.1789454.
Full textZollinger, Rachel, Mariko O. Thomas, Hollis Moore, and Kaitlin Bryson. "Lichenizing Pedagogy: Art Explorations in More-than-Human Performance and Practice." Research in Arts and Education 2022, no. 1 (May 27, 2022): 23–33. http://dx.doi.org/10.54916/rae.116995.
Full textDissertations / Theses on the topic "Visual and performative learning"
Zhu, Fan. "Visual feature learning." Thesis, University of Sheffield, 2015. http://etheses.whiterose.ac.uk/8218/.
Full textHuang, Wang. "Visual Sensation and Performative Cultural Politics: Chinese Literary Text Messages and the Colors of Texts." The Ohio State University, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=osu1275499580.
Full textGoh, Hanlin. "Learning deep visual representations." Paris 6, 2013. http://www.theses.fr/2013PA066356.
Full textRecent advancements in the areas of deep learning and visual information processing have presented an opportunity to unite both fields. These complementary fields combine to tackle the problem of classifying images into their semantic categories. Deep learning brings learning and representational capabilities to a visual processing model that is adapted for image classification. This thesis addresses problems that lead to the proposal of learning deep visual representations for image classification. The problem of deep learning is tackled on two fronts. The first aspect is the problem of unsupervised learning of latent representations from input data. The main focus is the integration of prior knowledge into the learning of restricted Boltzmann machines (RBM) through regularization. Regularizers are proposed to induce sparsity, selectivity and topographic organization in the coding to improve discrimination and invariance. The second direction introduces the notion of gradually transiting from unsupervised layer-wise learning to supervised deep learning. This is done through the integration of bottom-up information with top-down signals. Two novel implementations supporting this notion are explored. The first method uses top-down regularization to train a deep network of RBMs. The second method combines predictive and reconstructive loss functions to optimize a stack of encoder-decoder networks. The proposed deep learning techniques are applied to tackle the image classification problem. The bag-of-words model is adopted due to its strengths in image modeling through the use of local image descriptors and spatial pooling schemes. Deep learning with spatial aggregation is used to learn a hierarchical visual dictionary for encoding the image descriptors into mid-level representations. This method achieves leading image classification performances for object and scene images. The learned dictionaries are diverse and non-redundant. The speed of inference is also high. From this, a further optimization is performed for the subsequent pooling step. This is done by introducing a differentiable pooling parameterization and applying the error backpropagation algorithm. This thesis represents one of the first attempts to synthesize deep learning and the bag-of-words model. This union results in many challenging research problems, leaving much room for further study in this area
Walker, Catherine Livesay. "Visual learning through Hypermedia." CSUSB ScholarWorks, 1996. https://scholarworks.lib.csusb.edu/etd-project/1148.
Full textOwens, Andrew (Andrew Hale). "Learning visual models from paired audio-visual examples." Thesis, Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/107352.
Full textCataloged from PDF version of thesis.
Includes bibliographical references (pages 93-104).
From the clink of a mug placed onto a saucer to the bustle of a busy café, our days are filled with visual experiences that are accompanied by distinctive sounds. In this thesis, we show that these sounds can provide a rich training signal for learning visual models. First, we propose the task of predicting the sound that an object makes when struck as a way of studying physical interactions within a visual scene. We demonstrate this idea by training an algorithm to produce plausible soundtracks for videos in which people hit and scratch objects with a drumstick. Then, with human studies and automated evaluations on recognition tasks, we verify that the sounds produced by the algorithm convey information about actions and material properties. Second, we show that ambient audio - e.g., crashing waves, people speaking in a crowd - can also be used to learn visual models. We train a convolutional neural network to predict a statistical summary of the sounds that occur within a scene, and we demonstrate that the visual representation learned by the model conveys information about objects and scenes.
by Andrew Owens.
Ph. D.
Gontovnik, Monica. "Another Way of Being: The Performative Practices of Contemporary Female ColombianArtists." Ohio University / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1420473106.
Full textPeyre, Julia. "Learning to detect visual relations." Thesis, Paris Sciences et Lettres (ComUE), 2019. http://www.theses.fr/2019PSLEE016.
Full textIn this thesis, we study the problem of detection of visual relations of the form (subject, predicate, object) in images, which are intermediate level semantic units between objects and complex scenes. Our work addresses two main challenges in visual relation detection: (1) the difficulty of obtaining box-level annotations to train fully-supervised models, (2) the variability of appearance of visual relations. We first propose a weakly-supervised approach which, given pre-trained object detectors, enables us to learn relation detectors using image-level labels only, maintaining a performance close to fully-supervised models. Second, we propose a model that combines different granularities of embeddings (for subject, object, predicate and triplet) to better model appearance variation and introduce an analogical reasoning module to generalize to unseen triplets. Experimental results demonstrate the improvement of our hybrid model over a purely compositional model and validate the benefits of our transfer by analogy to retrieve unseen triplets
Tang-Wright, Kimmy. "Visual topography and perceptual learning in the primate visual system." Thesis, University of Oxford, 2016. https://ora.ox.ac.uk/objects/uuid:388b9658-dceb-443a-a19b-c960af162819.
Full textShi, Xiaojin. "Visual learning from small training datasets /." Diss., Digital Dissertations Database. Restricted to UC campuses, 2005. http://uclibs.org/PID/11984.
Full textLiu, Jingen. "Learning Semantic Features for Visual Recognition." Doctoral diss., University of Central Florida, 2009. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/3358.
Full textPh.D.
School of Electrical Engineering and Computer Science
Engineering and Computer Science
Computer Science PhD
Books on the topic "Visual and performative learning"
Black arts in Britain: Literary, visual, performative. Roma: Aracne, 2011.
Find full textImagining organizations: Performative imagery in business and beyond. New York, NY: Routledge, 2011.
Find full textK, Nayar Shree, and Poggio Tomaso, eds. Early visual learning. New York: Oxford University Press, 1996.
Find full textM, Moore David, and Dwyer Francis M, eds. Visual literacy: A spectrum of visual learning. Englewood Cliffs, N.J: Educational Technology Publications, 1994.
Find full textLiberty, Jesse. Learning Visual Basic .NET. Sebastopol, CA: O'Reilly, 2002.
Find full textLearning Visual Basic. NET. Beijing: O'Reilly, 2003.
Find full textN, Erin Jane, ed. Visual handicaps and learning. 3rd ed. Austin, Tex: PRO-ED, 1992.
Find full textLearning through visual displays. Charlotte, North Carolina: Information Age Publishing, Inc., 2013.
Find full textVisual impact, visual teaching: Using images to strengthen learning. San Diego, Calif: Brain Store, Inc., 2005.
Find full textVisual impact, visual teaching: Using images to strengthen learning. 2nd ed. Thousand Oaks, CA: Corwin Press, 2009.
Find full textBook chapters on the topic "Visual and performative learning"
Lähdesmäki, Tuuli, Jūratė Baranova, Susanne C. Ylönen, Aino-Kaisa Koistinen, Katja Mäkinen, Vaiva Juškiene, and Irena Zaleskiene. "Multimodality: Art as a Meaning-Making Process." In Learning Cultural Literacy through Creative Practices in Schools, 31–44. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-89236-4_3.
Full textCrowhurst, Michael, and Michael Emslie. "Performative Analysis." In Working Creatively with Stories and Learning Experiences, 27–37. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-69754-3_3.
Full textWulf, Christoph, Birgit Althans, Kathrin Audehm, and Juliane Engel. "Learning as a performative social process." In Learning as Social Practice, 103–45. Abingdon, Oxon ; New York, NY : Routledge, 2021. | Series: Foundations and futures of education: Routledge, 2021. http://dx.doi.org/10.4324/9781003139188-5.
Full textDahl, Thomas. "The poiesis and mimesis of learning." In Performative Approaches in Arts Education, 11–24. Abingdon, Oxon ; New York, NY : Routledge, 2019. | Series: Routledge research in education: Routledge, 2019. http://dx.doi.org/10.4324/9780429444159-2.
Full textWilliams, Julian, Julie Ryan, and Siân Morgan. "Lesson Study in a Performative Culture." In Workplace Learning in Teacher Education, 151–67. Dordrecht: Springer Netherlands, 2013. http://dx.doi.org/10.1007/978-94-007-7826-9_9.
Full textBurge, M., and W. Burger. "Learning visual ideals." In Image Analysis and Processing, 316–23. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/3-540-63508-4_138.
Full textBurge, M., and W. Burger. "Learning visual ideals." In Lecture Notes in Computer Science, 464–72. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/bfb0025067.
Full textPanciroli, Chiara, Laura Corazza, and Anita Macauda. "Visual-Graphic Learning." In Proceedings of the 2nd International and Interdisciplinary Conference on Image and Imagination, 49–62. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-41018-6_6.
Full textLu, Zhong-Lin, and Barbara Anne Dosher. "Visual Perceptual Learning." In Encyclopedia of the Sciences of Learning, 3415–18. Boston, MA: Springer US, 2012. http://dx.doi.org/10.1007/978-1-4419-1428-6_258.
Full textLovegrove, William. "The Visual Deficit Hypothesis." In Learning Disabilities, 246–69. New York, NY: Springer New York, 1992. http://dx.doi.org/10.1007/978-1-4613-9133-3_8.
Full textConference papers on the topic "Visual and performative learning"
Li, Shuwen. "Performative ePortfolio: A learning tool in technical and professional communication class." In 2016 IEEE Professional Communication Society (ProComm). IEEE, 2016. http://dx.doi.org/10.1109/ipcc.2016.7740492.
Full textLošonc, Alpar, Andrea Ivanišević, and Ivana Katić. "Economic discourse and visual configuration." In 10th International Symposium on Graphic Engineering and Design. University of Novi Sad, Faculty of technical sciences, Department of graphic engineering and design,, 2020. http://dx.doi.org/10.24867/grid-2020-p53.
Full textFratini, Nathalie. "PERFORMATIVE LEARNING METHODS IN VOCATIONAL EDUCATION AND TRAINING TO IMPROVE SOCIAL AND PERSONAL SKILLS." In 12th International Technology, Education and Development Conference. IATED, 2018. http://dx.doi.org/10.21125/inted.2018.0445.
Full textGimenez Calpe, Ana. "The Lecture-Performance: Implementing Performative Pedagogy in Literature Class." In Sixth International Conference on Higher Education Advances. Valencia: Universitat Politècnica de València, 2020. http://dx.doi.org/10.4995/head20.2020.11186.
Full textBuijs, Jean M., and Michael S. Lew. "Learning visual concepts." In the seventh ACM international conference. New York, New York, USA: ACM Press, 1999. http://dx.doi.org/10.1145/319878.319880.
Full textZhao, Qi, and Christof Koch. "Learning visual saliency." In 2011 45th Annual Conference on Information Sciences and Systems (CISS). IEEE, 2011. http://dx.doi.org/10.1109/ciss.2011.5766178.
Full textBERARDI, NICOLETTA, and ADRIANA FIORENTINI. "VISUAL PERCEPTUAL LEARNING." In Proceedings of the International School of Biophysics. WORLD SCIENTIFIC, 2001. http://dx.doi.org/10.1142/9789812799975_0034.
Full textGuida, Francesco Ermanno, and Ernesto Voltaggio. "Programming Visual Representations. Evolutions of Visual Identities between Tangible and Intangible." In Systems & Design: Beyond Processes and Thinking. Valencia: Universitat Politècnica València, 2016. http://dx.doi.org/10.4995/ifdp.2016.3334.
Full textGuangming Chang, Chunfen Yuan, and Weiming Hu. "Interclass visual similarity based visual vocabulary learning." In 2011 First Asian Conference on Pattern Recognition (ACPR 2011). IEEE, 2011. http://dx.doi.org/10.1109/acpr.2011.6166597.
Full textMahouachi, Dorra, and Moulay A. Akhloufi. "Deep learning visual programming." In Disruptive Technologies in Information Sciences III, edited by Misty Blowers, Russell D. Hall, and Venkateswara R. Dasari. SPIE, 2019. http://dx.doi.org/10.1117/12.2519882.
Full textReports on the topic "Visual and performative learning"
Bhanu, Bir. Learning Integrated Visual Database for Image Exploitation. Fort Belvoir, VA: Defense Technical Information Center, November 2002. http://dx.doi.org/10.21236/ada413389.
Full textEdelman, Shimon, Heinrich H. Buelthoff, and Erik Sklar. Task and Object Learning in Visual Recognition. Fort Belvoir, VA: Defense Technical Information Center, January 1991. http://dx.doi.org/10.21236/ada259961.
Full textJiang, Yuhong V. Implicit Learning of Complex Visual Contexts Under Non-Optimal Conditions. Fort Belvoir, VA: Defense Technical Information Center, July 2007. http://dx.doi.org/10.21236/ada482119.
Full textPoggio, Tomaso, and Stephen Smale. Hierarchical Kernel Machines: The Mathematics of Learning Inspired by Visual Cortex. Fort Belvoir, VA: Defense Technical Information Center, February 2013. http://dx.doi.org/10.21236/ada580529.
Full textHarmon, Dr Jennifer. Exploring the Efficacy of Active and Authentic Learning in the Visual Merchandising Classroom. Ames: Iowa State University, Digital Repository, November 2016. http://dx.doi.org/10.31274/itaa_proceedings-180814-1524.
Full textYu, Wanchi. Implicit Learning of Children with and without Developmental Language Disorder across Auditory and Visual Categories. Portland State University Library, January 2000. http://dx.doi.org/10.15760/etd.7460.
Full textKulhandjian, Hovannes. Detecting Driver Drowsiness with Multi-Sensor Data Fusion Combined with Machine Learning. Mineta Transportation Institute, September 2021. http://dx.doi.org/10.31979/mti.2021.2015.
Full textNahorniak, Maya. Occupation of profession: Methodology of laboratory classes from practically-oriented courses under distance learning (on an example of discipline «Radioproduction»). Ivan Franko National University of Lviv, February 2022. http://dx.doi.org/10.30970/vjo.2022.51.11412.
Full textAhmed AlGarf, Yasmine. From Self-Awareness to Purposeful Employment: Guiding Egyptian youth using arts-based learning. Oxfam IBIS, August 2021. http://dx.doi.org/10.21201/2021.7932.
Full textDale, Naomi, Aneesa Khan, and Sophie Dale. Early intervention for vision and neurodevelopment in infants and very young children with visual impairment: a systematicreview. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, August 2022. http://dx.doi.org/10.37766/inplasy2022.8.0080.
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