3D Modeling of Virtualized Reality Objects using Neural Computing

Authors(2) :-P. Sheepa, A. Charles

3D modeling of virtualized reality objects which follow a methodology using neural computing. In this paper, there are three acquisition systems: endoneurographic equipment (ENS), stereo vision system and non-contact 3D digitizer. The 3D virtualized representation correspond to several objects as phantom brain tumor, archaeological items, faces, things which have more complications This also comparison in terms of computational cost, architectural complexity, training methods, training epochs and performance. The research paper will conclude that it gives the best performance and the lowest displaying times, lowest memory requirements and acceptable training times with the help of the various methods used in this research paper.

Authors and Affiliations

P. Sheepa
Department of Computer Science, St. Joseph’s college, Trichy Tamilnadu, India
A. Charles
Department of Computer Science, St. Joseph’s college, Trichy Tamilnadu, India

Neural network, 3D model Endoneurosonographic system (ENS).

  1. Rüdiger W. Brause “ Medical Analysis and Diagnosis by Neural Networks” Medical Data Analysis, Volume 2199 of the series Lecture Notes in Computer Science pp 1-13.
  2. Heckerling, Canaris, Flach, Tape, Wigton and Gerber “Predictors of urinary tract infection based on artificial neural networks and genetic algorithms “ International Journal of Medical Informatics ,Volume 76, Issue 4, April 2007, Pp 289–296.
  3. Huang and Chen “Computer-aided diagnosis of urodynamic stress incontinence with vector-based perineal ultrasound using neural networks “, Volume 30, Issue 7 December 2007 Pp 1002–1006.
  4. P. Francisco, G. C. Juan Manuel, S. P. Antonio and R. F. “lower urinary tract based on artificial neural networks, Neurocomputing” , Jan., 2008, Vol. 71 Issue 4-6, pp. 743-754.
  5. A. Monadjemi and P. Moallem, “Automatic Diagnosis of Particular Diseases Using a Fuzzy-Neural Approach”, International Review on Computers & Software, Jul., 2008, Vol. 3 Issue 4, pp. 406-411.
  6. Gil, M. Johnsson, J. M. Garicia Chemizo, A. S. Paya and D. R. Fernandez, “Application of Artificial Neural Networks in the Diagnosis of Urological Dysfunctions, Expert Systems with Applications”, April, 2009, Vol. 36 Issue 3, pp. 5754-5760.
  7. Altunay, Z. Telatar, O. Erogul and E. Aydur, “A New Approach to urinary system dynamics problems: Evaluation and classification of uroflowmetric signals using artificial neural networks, Expert Systems with Applications “, April, 2009, Vol. 36 Issue 3, pp. 4891-4895.
  8. Moein, S. A. Monadjemi and P. Moallem,” A Novel Fuzzy-Neural Based Medical Diagnosis System”, International Journal of Biological & Medical Sciences", 2009, Vol. 4 Issue 3, pp. 146-150.
  9. Koushal Kumar,Abhishek “Artificial Neural Networks for Diagnosis of Kidney Stones Disease” IJITCS Vol. 4, No. 7, July 2012,  20-25.
  10. J.G. Lisboa," A review of evidence of health benefit from artificial neural networks in medical intervention", Volume 15, Issue 1, January 2002, Pages 11–39.

Publication Details

Published in : Volume 2 | Issue 4 | July-August 2016
Date of Publication : 2016-08-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 726-730
Manuscript Number : IJSRSET1624160
Publisher : Technoscience Academy

Print ISSN : 2395-1990, Online ISSN : 2394-4099

Cite This Article :

P. Sheepa, A. Charles, " 3D Modeling of Virtualized Reality Objects using Neural Computing, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 2, Issue 4, pp.726-730, July-August-2016.
Journal URL : http://ijsrset.com/IJSRSET1624160

Article Preview