1. 9) Nejad F. M. and Zakeri H. : A Comparison of Multi-resolution Methods for Detection and Isolation of Pavement Distress, Expart Systems with Applications, Vol. 38, pp. 2857-2872, 2011.
2. 11) Zhou J., Huang P. S., and Chiang F. P. : Wavelet-based Pavement Distress Detection and Evaluation, Optical Engineering, Vol. 45, No. 2, pp. 027007.1-027007.10, 2006.
3. 12) Hu Y. and Zhao C. : A Local Binary Pattern Based Methods for Pavement Crack Detection, Journal of Pattern Recognition Research, Vol. 5, No. 1, pp. 140-147, 2010.
4. 13) Wu L., Mokhtari S., Nazef A., Nam B., and Yun H. B. : Improvement of Crack-Detection Accuracy Using a Novel Crack Defragmentation Technique in Image-Based Road Assessment, Journal of Computing in Civil Engineering, 10.1061/(ASCE)CP.1943-5487.0000451, 04014118, 2014.
5. 15) LeCun, Y., Boser B. E., Denker J. S., Henderson D., Howard R. E., Hubbard W. E., and Jackel L. D. : Backpropagation applied to handwritten zip code recognition, Neural Computation, Vol. 1, No. 4, pp. 541-551, 1989.