Pre-processing of inputs to a neural network model for better performance in traffic scene analysis

References

• Arai , M. 1993 . Bounds on the number of hidden units in binary-valued three-layer neural networks . Neural Networks , 6 : 855 – 860 .
   Web of Science ®Google Scholar
• Balakrishnan , K. and Honavar , V. Improving convergence of backpropagation by handling flat-spots in the output layer . 2nd International Conference on Artificial Neural Networks , pp. 1003 – 1009 . Brighton, , UK
   Google Scholar
• Baum , E. B. and Haussler , D. 1989 . What size net gives valid generalisation? . Neural Computation , 1 : 151 – 160 .
   Web of Science ®Google Scholar
• Belgaroui , B. and Blosseville , J. 1993 . A road traffic application of neural techniques . Researche Transports Sécurité , : 53 – 65 . English Issue No. 9
   Google Scholar
• Bullock , D. , Garrett , J. J. and Hendrickson , C. 1993 . A neural network for image-based vehicle detection . Transportation Research C , 1 ( 3 ) : 235 – 247 .
   Google Scholar
• Fahlman , S. E. 1988 . An empirical study of learning speed in backpropagation networks , Carnegie Mellon University . Technical Report CMU-CS-88-162
   Google Scholar
• Faugeras , O. D. 1983 . Fundamentals in computer vision , Cambridge University Press .
   Google Scholar
• Fausett , L. 1994 . Fundamentals of neural networks: architectures, algorithms,and applications , Englewood Cliffs, NJ : Prentice-Hall .
   Google Scholar
• Gonzalez , R. C. and Woods , R. E. 1992 . Digital image processing , Reading, MA : Addison-Wesley .
   Google Scholar
• Kim , D. 1999 . Problems encountered during implementation of the backpropagation . ITS Journal , 5 ( 1 ) : 71 – 86 .
   Google Scholar
• Kim , D. 2001 . Performance comparison of neural network models: backpropagation vs. fuzzy artmap . International Journal of Computer Mathematics , 78 : 365 – 382 .
   Web of Science ®Google Scholar
• Kim , D. 2002 . Standard and advanced backpropagation models for image processing application in traffic engineering . ITS Journal , 7 ( 3–4 ) : 199 – 211 .
   Google Scholar
• Kim , D. and Bell , M. G.H. 1997 . “ Parking vacancy detection using image processing and neural networks ” . In 4th ITS World Congress Berlin
   Google Scholar
• Lippmann , R. P. 1987 . An introduction to computing with neural nets . IEEE Acoustics, Speech and Signal Processing Magazine , 4 ( 2 ) : 4 – 22 .
   Google Scholar
• Pal , N. R. and Pal , S. K. 1993 . A review on image segmentation techniques . Pattern Recognition , 26 ( 9 ) : 1277 – 1294 .
   Web of Science ®Google Scholar
• Papageorgiou , C. P. and Poggio , T. 1999 . A trainable object detection system: car detection in static images , MIT AI Memo No. 180, October
   Google Scholar
• Rumelhart , D. E. , Hinton , G. E. and McClelland , J. L. 1986a . “ A general framework for parallel distributed processing ” . In Parallel distributed processing , Edited by: Rumelhart , D. E. and McClelland , J. L. Vol. 1 , 45 – 76 . Cambridge, MA : MIT Press . the PDP Research Group
   Google Scholar
• Rumelhart , D. E. , Hinton , G. E. and Williams , R. J. 1986b . “ Learning internal representations by error propagation ” . In Parallel distributed processing , Edited by: Rumelhart , D. E. and McClelland , J. L. Vol. 1 , 318 – 364 . Cambridge, MA : MIT Press . the PDP Research Group
   Google Scholar
• Sun , Z. , Bebis , G. and Miller , R. 2005 . On-road vehicle detection using evolutionary Gabor filter optimization . IEEE Transactions on Intelligent Transportation Systems , 6 ( 2 ) : 125 – 137 .
   Web of Science ®Google Scholar
• Wan , C. L. and Dickinson , K. W. Computer vision and neural networks for traffic monitoring . 6th IEE International Conference on Road Traffic Monitoring and Control . pp. 143 – 147 . London
   Google Scholar
• Widrow , B. ADALINE and MADALINE –1963 . 1st IEEE International Conference on Neural Networks . Vol. 1 , pp. 143 – 157 . San Diego, CA
   Google Scholar
• Wieland , A. and Leighton , R. Geometric analysis of neural network capabilities . 1st IEEE International Conference on Neural Networks . Vol. 3 , pp. 385 – 392 . San Diego, CA
   Google Scholar