Adaptive committees of feature-specific classifiers for image classification

Proceedings of the 2nd International Workshop on Image Mining Theory and Applications, IMTA 2009 In Conjunction with VISIGRAPP 2009

Volumn , Issue , 2009, Pages 113-122

  Fagni, Tiziano ^a   Falchi, Fabrizio ^a   Sebastiani, Fabrizio ^a  

^a CNR   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

ACCURACY IMPROVEMENT; ADAPTIVE COMMITTEES;

CLASSIFIERS; IMAGE ANALYSIS; LEARNING SYSTEMS; MINING; MOTION PICTURE EXPERTS GROUP STANDARDS;

IMAGE CLASSIFICATION;

EID: 67650548640     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (15)

1. Lu, D., Weng, Q.: A survey of image classification methods and techniques for improving classification performance. International Journal of Remote Sensing 28(5) (2007) 823-870 (Pubitemid 46476334)
2. Giacinto, G., Roli, R: Adaptive selection of image classifiers. In: Proceedings of the 9th International Conference on Image Analysis and Processing (ICIAP'97), Firenze, IT (1997) 38-45 (Pubitemid 127124594)
3. Li, Y.H., Jain, A.K.: Classification of text documents. The Computer Journal 41(8) (1998) 537-546
4. Woods, K., Kegelmeyer Jr, W., Bowyer, K.: Combination of multiple classifiers using local accuracy estimates. IEEE Transactions on Pattern and Machine Intelligence 19(4) (1997) 405-410 (Pubitemid 127762896)
5. Schapire, R.E., Singer, Y.: Improved boosting using confidence-rated predictions. Machine Learning 37(3) (1999) 297-336 (Pubitemid 32210620)
6. Joachims, T.: Text categorization with support vector machines: Learning with many relevant features. In: Proceedings of the 10th European Conference on Machine Learning (ECML'98), Chemnitz, DE (1998) 137-142 (Pubitemid 128067178)
7. Yang, Y: An evaluation of statistical approaches to text categorization. Information Retrieval 1(1/2) (1999) 69-90
8. Yang, Y, Liu, X.: A re-examination of text categorization methods. In: Proceedings of the 22nd ACM International Conference on Research and Development in Information Retrieval (SIGIR'99), Berkeley, US (1999) 42-49
9. Yang, Y, Zhang, J., Kisiel, B.: A scalability analysis of classifiers in text categorization. In: Proceedings of the 26th ACM International Conference on Research and Development in Information Retrieval (SIGIR'03), Toronto, CA (2003) 96-103
10. Ch-vez, E., Navarro, G., Baeza-Yates, R., Marroquln, J.L.: Searching in metric spaces. ACM Computing Surveys 33(3) (2001) 273-321 (Pubitemid 33768485)
11. Samet, H.: Foundations of Multidimensional and Metric Data Structures. Morgan Kaufmann, San Francisco, US (2006)
12. Zezula, P., Amato, G., Dohnal, V., Batko, M.: Similarity Search: The Metric Space Approach. Springer Verlag, Heidelberg, DE (2006)
13. Ciaccia, P., Patella, M., Zezula, P.: M-tree: An efficient access method for similarity search in metric spaces. In: Proceedings of the 23rd International Conference on Very Large Data Bases (VLDB '97), Athens, GR (1997) 426-435
14. Manjunath, B., Salembier, P., Sikora, T., eds.: Introduction to MPEG-7: Multimedia Content Description Interface. John Wiley & Sons, New York, US (2002)
15. Amato, G., Falchi, R, Gennaro, C, Rabitti, F., Savino, P., Stanchev, P.: Improving image similarity search effectiveness in a multimedia content management system. In: Proceedings of the 10th International Workshop on Multimedia Information System (MIS'04), College Park, US (2004) 139-146