Neuro System Structure for Vehicle Recognition and Count in Floating Bridge Specific Conditions

  • Slobodan Beroš
  • Saša Mladenović
  • Špiro Matošin


The paper presents the research of the sophisticated vehiclerecognition and count system based on the application of theneural network. The basic elements of neural network andadaptive logic network for object recognition are discussed. Theadaptive logic network solution ability based on simple digitalcircuits as crucial in real-time applications is pointed out. Thesimulation based on the use of reduced high level noise pictureand a tree 2. 7. software have shown excellent results. The consideredand simulated adaptive neural network based systemwith its good recognition and convergence is a useful real-timesolution for vehicle recognition and count in the floating bridgesevere conditions.


I. Dekovic, Prepoznavanje oblika temeljeno na neizrazitoj

logici i neuralnim strukturama. Magistarski rad, FESB,

Sveuciliste u Splitu, 1994.

W.S. McCulloch and W. Pitts, 'A logical calculus of the

ideas immanent in neurons activity'. Bulletin of Mathematical

Biophysics, Nr. 5, 1943, pp. 115-133.

F. Rosenblatt, Principles of Neurodynamics. Washington

DC: Spartan Books, 1962.

B, Widrow, Generalization and information Storage in

networks of adaline 'neurons' In Self-Organizing Systems

pp. 435-461, W.DC Sparta 1962.

S. Haykin, Neural Networks a comprehensive Foundation,

IEEE Computer Society Press, New York 1994.

J. Hertz, A. Krogh, R.g. Palmer, 'Introduction to the

Theory of Neural Computation', Addison-Wesley,

Reading, Mass., 1991.

R.P. Lippmann, ''An introduction to Computing with

Neural Nets', IEEE ASSP Magazine, April 1987, pp.

A. K. Jain, J. Mao, 'Artificial Neural Networks: A Tutorial'',

IEEE Computer Magazine, March 1996, pp.


W. W. Armstrong atree 2.7.1995.

W. W. Armstrong, J. Gecsei,Adaption algorithms for Binary

Tree Networks, IEEE Trans. on Systems, Man and

Cybernetics, 9, 1979, pp. 276-285.

ftp atree.Z., 1996.

Dendronic Decisions Limited, 3624 - 108 Street, Edmond,

Alberta, Canada T6J 1B4,

W. Armstrong, J.-D. Liang, D. Lin, S. Reynolds,Erperiments

Using Parsimonious Adaptive Logic, Tech. Rept.

TR 90-30, Department of Computing Science, University

of Alberta, Edmonton, Alberta, Canada, T6G 2H1,

Dean A. Pomerlan, 'Neural Networks for Intelligent Vehicles',

Neural Networks Applications, lEE Technology

update series, 1996, p.p. 927-932.

S. Matosin, Teorija pontonskog mosta u morskim

uvjetima, Ceste i mostovi, Nr. 5-6, 1995, str. 135-156.

How to Cite
Beroš S, Mladenović S, Matošin Špiro. Neuro System Structure for Vehicle Recognition and Count in Floating Bridge Specific Conditions. PROMET [Internet]. 1 [cited 2019Jun.19];9(3):113-20. Available from:
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