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Relevant bibliographies by topics / Visual modelling / Journal articles

Journal articles on the topic 'Visual modelling'

To see the other types of publications on this topic, follow the link: Visual modelling.

Author: Grafiati

Published: 4 June 2021

Last updated: 4 February 2022

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1

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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2

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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3

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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4

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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5

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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6

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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7

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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8

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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9

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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10

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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11

Muetzelfeldt, Robert, and Jon Massheder. "The Simile visual modelling environment." European Journal of Agronomy 18, no. 3-4 (January 2003): 345–58. http://dx.doi.org/10.1016/s1161-0301(02)00112-0.

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12

Gaillard, B., and J. Feng. "Modelling a visual discrimination task." Neurocomputing 65-66 (June 2005): 203–9. http://dx.doi.org/10.1016/j.neucom.2004.10.008.

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13

Kato, Toshikazu. "Modelling a Visual Sense Process." Journal of the Society of Mechanical Engineers 98, no. 918 (1995): 400–402. http://dx.doi.org/10.1299/jsmemag.98.918_400.

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14

Moreno-Díaz, Roberto, and Gabriel De Blasio. "Systems Methods in Visual Modelling." Systems Analysis Modelling Simulation 43, no. 9 (September 2003): 1159–71. http://dx.doi.org/10.1080/02329290310001600255.

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15

Copperman, Elana, Catriel Beeri, and Nava Ben‐Zvi. "Visual modelling of learning processes." Innovations in Education and Teaching International 44, no. 3 (August 2007): 257–72. http://dx.doi.org/10.1080/14703290701486571.

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16

Bottoni, Paolo. "Dynamic aspects of visual modelling languages." Electronic Notes in Theoretical Computer Science 82, no. 7 (June 2003): 120–32. http://dx.doi.org/10.1016/s1571-0661(04)80751-5.

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17

Wiebe, Kevin James, and Anup Basu. "Modelling ecologically specialized biological visual systems." Pattern Recognition 30, no. 10 (October 1997): 1687–703. http://dx.doi.org/10.1016/s0031-3203(96)00160-4.

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18

Pal, R., A. Mukherjee, P. Mitra, and J. Mukherjee. "Modelling visual saliency using degree centrality." IET Computer Vision 4, no. 3 (2010): 218. http://dx.doi.org/10.1049/iet-cvi.2009.0067.

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19

Pollefeys, Marc, and Luc Van Gool. "Visual modelling: from images to images." Journal of Visualization and Computer Animation 13, no. 4 (2002): 199–209. http://dx.doi.org/10.1002/vis.289.

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20

Shen, Jianhong, and Thomas J. Palmeri. "Modelling individual difference in visual categorization." Visual Cognition 24, no. 3 (March 15, 2016): 260–83. http://dx.doi.org/10.1080/13506285.2016.1236053.

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21

Billington, J. N. "Visual interactive modelling and manpower planning." European Journal of Operational Research 30, no. 1 (June 1987): 77–84. http://dx.doi.org/10.1016/0377-2217(87)90013-0.

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22

Voorhees, B. "Symmetric group modelling of visual information." Il Nuovo Cimento B Series 11 106, no. 10 (October 1991): 1067–78. http://dx.doi.org/10.1007/bf02728352.

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23

Bottoni, P., M. F. Costabile, and S. Levialdi. "Analyzing, modelling, and specifying visual interaction." Soft Computing 7, no. 1 (November 2002): 9–19. http://dx.doi.org/10.1007/s00500-002-0168-8.

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24

Chen, Duan-Yu. "Modelling salient visual dynamics in videos." Multimedia Tools and Applications 53, no. 1 (March 24, 2010): 271–84. http://dx.doi.org/10.1007/s11042-010-0511-5.

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25

Unzicker, Alexander, Martin Jüttner, and Ingo Rentschler. "Modelling the dynamics of visual classification learning." Mathematical Social Sciences 38, no. 3 (November 1999): 295–313. http://dx.doi.org/10.1016/s0165-4896(99)00022-0.

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26

Power, John, and Konstantinos Tourlas. "On the Geometric Modelling of Visual Languages." Electronic Notes in Theoretical Computer Science 72, no. 3 (February 2003): 1–12. http://dx.doi.org/10.1016/s1571-0661(04)80607-8.

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27

Leung, V., A. Colombo, J. Orwell, and S. A. Velastin. "Modelling periodic scene elements for visual surveillance." IET Computer Vision 2, no. 2 (2008): 88. http://dx.doi.org/10.1049/iet-cvi:20070070.

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28

Lillehagen, Frank, John Krogstie, and Helge Grenager Solheim. "From enterprise modelling to enterprise visual scenes." International Journal of Internet and Enterprise Management 3, no. 2 (2005): 139. http://dx.doi.org/10.1504/ijiem.2005.007637.

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29

Šetić, Mia, Domagoj Švegar, and Dražen Domijan. "Modelling the statistical processing of visual information." Neurocomputing 70, no. 10-12 (June 2007): 1808–12. http://dx.doi.org/10.1016/j.neucom.2006.10.069.

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30

Heuvelink, EP, J. H. Lee, and S. M. P. Carvalho. "MODELLING VISUAL PRODUCT QUALITY IN CUT CHRYSANTHEMUM." Acta Horticulturae, no. 566 (December 2001): 77–84. http://dx.doi.org/10.17660/actahortic.2001.566.7.

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31

Koonce, David A., and Robert P. Judd. "A visual modelling language for EXPRESS schema." International Journal of Computer Integrated Manufacturing 14, no. 5 (January 2001): 457–72. http://dx.doi.org/10.1080/09511920010022495.

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32

Rathnam, Sukumar, and T. Madhavan. "An interactive graphics based visual modelling tool." Mathematical and Computer Modelling 16, no. 4 (April 1992): 115–29. http://dx.doi.org/10.1016/0895-7177(92)90039-n.

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33

Bishop, B., S. Hutchinson, and M. Spong. "Camera modelling for visual servo control applications." Mathematical and Computer Modelling 24, no. 5-6 (September 1996): 79–102. http://dx.doi.org/10.1016/0895-7177(96)00116-1.

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34

Chen, J., M. Yeasin, and R. Sharma. "Visual modelling and evaluation of surgical skill." Pattern Analysis & Applications 6, no. 1 (April 22, 2003): 1–11. http://dx.doi.org/10.1007/s10044-002-0165-7.

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35

Zhang, Lianfeng. "Modelling process platforms based on an object-oriented visual diagrammatic modelling language." International Journal of Production Research 47, no. 16 (June 3, 2009): 4413–35. http://dx.doi.org/10.1080/00207540801950144.

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36

Ljungholm, Mikael, and Dan-E. Nilsson. "Modelling the visual world of a velvet worm." PLOS Computational Biology 17, no. 7 (July 28, 2021): e1008808. http://dx.doi.org/10.1371/journal.pcbi.1008808.

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Abstract:

In many animal phyla, eyes are small and provide only low-resolution vision for general orientation in the environment. Because these primitive eyes rarely have a defined image plane, traditional visual-optics principles cannot be applied. To assess the functional capacity of such eyes we have developed modelling principles based on ray tracing in 3D reconstructions of eye morphology, where refraction on the way to the photoreceptors and absorption in the photopigment are calculated incrementally for ray bundles from all angles within the visual field. From the ray tracing, we calculate the complete angular acceptance function of each photoreceptor in the eye, revealing the visual acuity for all parts of the visual field. We then use this information to generate visual filters that can be applied to high resolution images or videos to convert them to accurate representations of the spatial information seen by the animal. The method is here applied to the 0.1 mm eyes of the velvet worm Euperipatoides rowelli (Onychophora). These eyes of these terrestrial invertebrates consist of a curved cornea covering an irregular but optically homogeneous lens directly joining a retina packed with photoreceptive rhabdoms. 3D reconstruction from histological sections revealed an asymmetric eye, where the retina is deeper in the forward-pointing direction. The calculated visual acuity also reveals performance differences across the visual field, with a maximum acuity of about 0.11 cycles/deg in the forward direction despite laterally pointing eyes. The results agree with previous behavioural measurements of visual acuity, and suggest that velvet worm vision is adequate for orientation and positioning within the habitat.

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37

Rai, Ankush, and Jagadeesh Kannan R. "NEUROCOMPUTATIONAL MODELLING OF DISTRIBUTED LEARNING FROM VISUAL STIMULI." Asian Journal of Pharmaceutical and Clinical Research 10, no. 13 (April 1, 2017): 225. http://dx.doi.org/10.22159/ajpcr.2017.v10s1.19645.

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Neurocomputational modeling of visual stimuli can lead not only to identify the neural substrates of attention but also to test cognitive theories ofattention with applications on several visual media, robotics, etc. However, there are many research works done in cognitive model for linguistics,but the studies regarding cognitive modeling of learning mechanisms for visual stimuli are falling back. Based on principles of operation cognitivefunctionalities in human vision processing, the study presents the development of a computational neurocomputational cognitive model for visualperception with detailed algorithmic descriptions. Here, four essential questions of cognition and visual attention is considered for logicallycompressing into one unified neurocomputational model: (i) Segregation of special classes of stimuli and attention modulation, (ii) relation betweengaze movements and visual perception, (iii) mechanism of selective stimulus processing and its encoding in neuronal cells, and (iv) mechanism ofvisual perception through autonomous relation proofing.

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38

Los’, A. L. "LINGUUISTIC MODELLING OF AUDITORY AND VISUAL PERCEPTION SITUATIONS." Voprosy Kognitivnoy Lingvistiki, no. 2 (2020): 125–31. http://dx.doi.org/10.20916/1812-3228-2020-2-125-131.

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39

Kim, Y. H., and C. S. Wardle. "Modelling the visual stimulus of towed fishing gear." Fisheries Research 34, no. 2 (March 1998): 165–77. http://dx.doi.org/10.1016/s0165-7836(97)00089-1.

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40

Lanyon, Linda J., and Susan L. Denham. "Modelling Visual Neglect: Computational Insights into Conscious Perception." PLoS ONE 5, no. 6 (June 15, 2010): e11128. http://dx.doi.org/10.1371/journal.pone.0011128.

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41

Hoppe, David, and Constantin Rothkopf. "Modelling the dynamics of visual attention under uncertainty." Journal of Vision 15, no. 12 (September 1, 2015): 566. http://dx.doi.org/10.1167/15.12.566.

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42

Giordano, Massimiliano, Giuseppe Polese, Giuseppe Scanniello, and Genoveffa Tortora. "A system for visual role-based policy modelling." Journal of Visual Languages & Computing 21, no. 1 (February 2010): 41–64. http://dx.doi.org/10.1016/j.jvlc.2009.11.002.

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43

Collins, Trevor D., and Pat Fung. "A visual programming approach for teaching cognitive modelling." Computers & Education 39, no. 1 (August 2002): 1–18. http://dx.doi.org/10.1016/s0360-1315(01)00087-2.

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44

Kokkinara, Elena, Oyewole Oyekoya, and Anthony Steed. "Modelling selective visual attention for autonomous virtual characters." Computer Animation and Virtual Worlds 22, no. 4 (July 2011): 361–69. http://dx.doi.org/10.1002/cav.425.

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45

Garcia-Perez, Miguel A. "The perceived image: Efficient modelling of visual inhomogeneity." Spatial Vision 6, no. 2 (1992): 89–99. http://dx.doi.org/10.1163/156856892x00163.

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46

Mäkelä, Pia, David Whitaker, and Jyrki Rovamo. "Modelling of orientation discrimination across the visual field." Vision Research 33, no. 5-6 (March 1993): 723–30. http://dx.doi.org/10.1016/0042-6989(93)90192-y.

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47

Chamorro-Martínez, Jesús, Pedro Manuel Martínez-Jiménez, José Manuel Soto-Hidalgo, and Alejandro León Salas. "A fuzzy approach for modelling visual texture properties." Information Sciences 313 (August 2015): 1–21. http://dx.doi.org/10.1016/j.ins.2015.03.058.

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48

Chamorro-Martínez, Jesús, Pedro Manuel Martínez-Jiménez, José Manuel Soto-Hidalgo, and Belén Prados-Suárez. "Perception-based fuzzy sets for visual texture modelling." Soft Computing 18, no. 12 (February 9, 2014): 2485–99. http://dx.doi.org/10.1007/s00500-014-1226-8.

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49

Seron, F. J., J. J. Torrens, J. A. Magallon, A. Turon, and S. Baldassarri. "Geometric and visual modelling of complex stratigraphic structures." Computers & Graphics 28, no. 4 (August 2004): 585–99. http://dx.doi.org/10.1016/j.cag.2004.04.013.

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50

Tan, T. N. "Texture edge detection by modelling visual cortical channels." Pattern Recognition 28, no. 9 (September 1995): 1283–98. http://dx.doi.org/10.1016/0031-3203(94)00017-g.

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