Books on the topic 'Mathematical perception'

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1

Pentland, Alexander. The parts of perception. Menlo Park, CA: Center for the Study of Language and Information/SRI International, 1987.

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2

Music: A mathematical offering. Cambridge, UK: Cambridge University Press, 2007.

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3

1932-, Dutta Majumder D., ed. Fuzzy mathematical approach to pattern recognition. New York: Wiley, 1986.

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4

Berendt, Bettina. Representation and processing of knowledge about distances in environmental spaces: A computational model of inferred route distances investigating their qualitative and quantitiative determinants. Frankfurt am Main: Infix, 1999.

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5

Tsotsos, John Konstantine. The complexity of perceptual search tasks. Toronto: University of Toronto, Dept. of Computer Science, 1989.

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6

General pattern theory: A mathematical study of regular structures. Oxford: Clarendon, 1993.

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7

Norwich, Kenneth H. Information, sensation, and perception. San Diego, CA: Academic Press, 1993.

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8

D, Hoffman Donald, and Prakash Chetan, eds. Observer mechanics: A formal theory of perception. San Diego: Academic Press, 1989.

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9

Alwar, M. A. Pratyaksam: Bharatiyadarsana-ganakayantravijnanayordrstya samiksa. Tirupatih: Rastriyasamskrtavidyapitham, 2010.

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10

Pratyaksam: Bharatiyadarsana-ganakayantravijnanayordrstya samiksa. Tirupatih: Rastriyasamskrtavidyapitham, 2010.

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11

Jepson, Allan D. What is a percept? Toronto: University of Toronto, Dept. of Computer Science, 1993.

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12

Betelin, V. B. Raspoznavanie videograficheskoĭ informat︠s︡ii. Moskva: Nauchnyĭ sovet po kompleksnoĭ probleme "Kibernetika" RAN, 1999.

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13

Pienkowski, Andrew E. K. Artificial colour perception using fuzzy techniques in digital image processing. Köln: Verlag TÜV Rheinland, 1989.

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14

Jenkin, Michael R. M. Techniques for disparity measurement. Toronto: University of Toronto, Dept. of Computer Science, 1987.

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15

Jepson, Allan D. Mixture models for optical flow computation. Toronto: University of Toronto, Dept. of Computer Science, 1993.

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16

Pattern puzzles. London: Franklin Watts, 2015.

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17

Eindhoven), Working Models of Human Perception (1987. Working models of human perception. London: Academic, 1989.

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18

Fleet, David J. Computation of normal velocity from local phase information. Toronto: University of Toronto, Dept. of Computer Science, 1989.

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19

1938-, Hawkins Harold L., ed. Auditory computation. New York: Springer Verlag, 1996.

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20

Barberis, Nicholas. The loss aversion narrow framing approach to the equity premium puzzle. Cambridge, Mass: National Bureau of Economic Research, 2006.

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21

Petitot, Jean. Neurogéométrie de la vision: Modèles mathématiques et physiques des architectures fonctionnelles. [Palaiseau]: Les Éditions de l'École Polytechnique, 2008.

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22

International Federation of Classification Societies. Conference. Classification, clustering and data analysis: Recent advances and applications. Berlin: Springer, 2002.

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23

Metod komitetov v zadachakh optimizat͡s︡ii i klassifikat͡s︡ii. Moskva: "Nauka," Glav. red. fiziko-matematicheskoĭ lit-ry, 1990.

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24

V, Zolotov E., ed. Teoretiko-igrovye raspoznai͡u︡shchie algoritmy. Moskva: "Nauka", 1990.

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25

Sōtaiteki hakudatsu no shakaigaku: Fubyōdō to ishiki no paradokkusu = A sociology of relative deprivation : paradoxes of inequality and perception. Tōkyō-to Meguro-ku: Tōkyō Daigaku Shuppankai, 2015.

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26

Koski, Toivo. Success potential of a venture capital investment: A model to simulate venture capitalists' perception using fuzzy set theory. [Helsinki]: Helsinki School of Economics and Business Administration, 2000.

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27

Linnanmäki, Karin. Matematikprestationer och självuppfattning: En uppföljningsstudie i relation till skolspråk och kön. Åbo: Åbo Akademis förlag, 2002.

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28

V, Koutras Markos, ed. Runs and scans with applications. New York: J. Wiley, 2002.

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29

Basu, Kaushik. Punctuality: A cultural trait as equilibrium. Cambridge, MA: Massachusetts Institute of Technology, Dept. of Economics, 2002.

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30

Barron, John Leonard. Computing motion and structure from noisy, time-varying image velocity information. Toronto: University of Toronto, Dept. of Computer Science, 1988.

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31

Symposium on Noise and Disorder in Vision (1987 Toronto, Ont.). Symposium on Noise and Disorder in Vision: 1987 lectures in vision, University of Toronto. Toronto: University of Toronto, Dept. of Computer Science, 1987.

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32

J, Wenger Michael, and Townsend James T, eds. Computational, geometric, and process perspectives on facial cognition: Contexts and challenges. Mahwah, N.J: L. Erlbaum Associates, 2001.

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33

A computational perspective on visual attention. Cambridge, Mass: MIT Press, 2011.

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34

International Federation of Classification Societies. Conference. Program and abstracts: IFCS 2002 : data analysis, classification, and related methods : 8th Conference of the International Federation of Classification Societies, July 16-19, 2002, Cracow, Poland. Cracow: University of Economics Publishers, 2002.

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35

Measurements with persons: Theory, methods, and implementation areas. New York: Psychology Press, 2011.

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36

Sargent, Brian. Grandfather's shape story. New York: Children's Press, 2006.

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37

1959-, Valentine Tim, British Psychological Society. Welsh Branch., and International Conference on Face Processing (1993 : Cardiff, Wales), eds. Cognitive and computational aspects of face recognition: Explorations in face space. London: Routledge, 1995.

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38

Sargent, Brian. Grandfather's shape story. New York: Children's Press, 2007.

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39

Volkova, Tat'yana. Course of mathematical analysis for undergraduate students of engineering faculties. ru: INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1013010.

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The textbook is prepared on the basis of lectures on mathematical analysis given by the author. The mathematical formalism of the presentation of classical textbooks is not suitable for the perception of a modern student, so the material is presented in a concise and more accessible form for assimilation. Meets the requirements of the federal state educational standards of higher education of the latest generation. For undergraduate students studying in the areas of "Information Systems and Technologies" and "Computer Science and Computer Engineering".
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40

Angstenberger, Larisa. Dynamic Fuzzy Pattern Recognition with Applications to Finance and Engineering. Dordrecht: Springer Netherlands, 2001.

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41

service), SpringerLink (Online, ed. Circuits in the Brain: A Model of Shape Processing in the Primary Visual Cortex. New York, NY: Springer-Verlag New York, 2009.

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42

Tsotsos, John Konstantine. Analyzing vision at the complexity level: Constrains on an architecture, an explanation for visual search performance, and computational justification for attentive processes. Toronto: University of Toronto, Dept. of Computer Science, 1987.

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43

Houpt, Joseph W., and Leslie M. Blaha. Mathematical Models of Perception and Cognition Volume II. Taylor & Francis Group, 2018.

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44

Houpt, Joseph W., and Leslie M. Blaha. Mathematical Models of Perception and Cognition Volume I. Taylor & Francis Group, 2018.

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45

Houpt, Joseph. Mathematical Models of Perception and Cognition Volume II. Routledge, 2016. http://dx.doi.org/10.4324/9781315647265.

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46

Houpt, Joseph. Mathematical Models of Perception and Cognition Volume I. Psychology Press, 2016. http://dx.doi.org/10.4324/9781315647272.

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47

Grenander, Ulf. General Pattern Theory: A Mathematical Study of Regular Structures (Oxford Mathematical Monographs). Oxford University Press, USA, 1994.

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48

Sawada, Tadamasa, Yunfeng Li, and Zygmunt Pizlo. Shape Perception. Edited by Jerome R. Busemeyer, Zheng Wang, James T. Townsend, and Ami Eidels. Oxford University Press, 2015. http://dx.doi.org/10.1093/oxfordhb/9780199957996.013.12.

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This chapter provides a review of topics and concepts that are necessary to study and understand 3D shape perception. This includes group theory and their invariants; model-based invariants; Euclidean, affine, and projective geometry; symmetry; inverse problems; simplicity principle; Fechnerian psychophysics; regularization theory; Bayesian inference; shape constancy and shape veridicality; shape recovery; perspective and orthographic projections; camera models; as well as definitions of shape. All concepts are defined and illustrated, and the reader is provided with references providing mathematical and computational details. Material presented here will be a good starting point for students and researchers who plan to study shape, as well as for those who simply want to get prepared for reading the contemporary literature on the subject.
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49

Shafarenko, Leila. Perception-driven automatic segmentation of colour images using mathematical morphology. 1996.

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50

Morphing: A Guide to Mathematical Transformations for Architects and Designers. King Publishing, Laurence, 2015.

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