Committee machine for road-signs classification

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 4029 LNAI, Issue , 2006, Pages 583-592

  Cyganek, Bogusław ^a  

^a AGH UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Poland)

Author keywords

[No Author keywords available]

Indexed keywords

ACCIDENT PREVENTION; ARTIFICIAL INTELLIGENCE; AUTOMOBILE DRIVERS; NEURAL NETWORKS; RESPONSE TIME (COMPUTER SYSTEMS);

EUCLIDEAN DISTANCE NEURAL NETWORKS; HAMMING NEURAL NETWORKS; ROAD-SIGNS CLASSIFICATION;

TRAFFIC SIGNS;

EID: 33746257760     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11785231_61     Document Type: Conference Paper

References (15)

1. Aoyagi, Y., Asakura, T.: A study on traffic sign recognition in scene image using genetic algorithms and neural networks, IEEE Conf. Electronics (1996) 1838-1843
2. Chen, X., Yang, J., Zhang, J., Waibel, A.: Automatic Detection and Recognition of Signs From Natural Scenes. IEEE Trans. on Image Proc. 13(1) (2004) 87-99
3. Cyganek, B.: Object Detection in Multi-Channel and Multi-Scale Images Based on the Structural Tensor. Springer LNCS 3691 (2005) 570-578
4. Duch, W., Grudziski, K.: A framework for similarity-based methods. Second Polish Conference on Theory and Applications of Artificial Intelligence (1998) 33-60
5. Escalera, A., Moreno, L., Salichs, M., Armingol, J.: Road traffic sign detection and classification. IEEE Trans. Ind. Electron., v.44 (1997) 848-859
6. Escalera, A., Armingol, J.: Visual Sign Information Extraction and Identification by Deformable Models. IEEE Tr. On Int. Transportation, 5(2) (2004) 57-68
7. Floréen, P.: Computational Complexity Problems in Neural Associative Memories. PhD Thesis, University of Helsinki, Finland (1992)
8. Lippman, R.: An introduction to computing with neural nets. IEEE Transactions on Acoustic, Speech, and Signal Processing, v.ASSP-4 (1987) 4-22
9. Luo, R., Potlapalli, H., Hislop, D.: Neural network based landmark recognition for robot navigation. IEEE Int. Conf, Industrial Electronics (1992) 1084-1088
10. Luo, R., Potlapalli, H.: Landmark recognition using projection learning for mobile robot navigation. In Proc. IEEE Int, Conf. Neural Networks (1994) 2703-2708
11. Piccioli, G., Micheli, E.D., Parodi, P., Campani, M.: Robust method for road sign detection and recognition. Image and Vision Computing, v.14 (1996) 209-223
12. Road Signs and Signalization. Directive of the Polish Ministry of Infrastructure. Internal Affairs and Administration (Dz. U. Nr 170, poz, 1393) (2002)
13. Rehrmann, V., Lakmann, R., Priese, A.: A parallel system for real-time traffic sign recognition. Deimler-Benz Technical Report (1995)
14. Viola, P., Jones, M.: Rapid Object Detection using a Boosted Cascade of Simple Features. IEEE Conf. on Computer Vision and Pattern Recognition (2001) 151-158
15. Zheng, Y. J., Ritter, W., Janssen, R.: An adaptive system for traffic sign recognition. Proc. IEEE Intelligent Vehicles Symp. (1994) 165-170