Combining flat and structured representations for fingerprint classification with recursive neural networks and support vector machines

Pattern Recognition

Volumn 36, Issue 2, 2003, Pages 397-406

  Yao, Yuan ^a   Marcialis, Gian Luca ^b   Pontil, Massimiliano ^a,c   Frasconi, Paolo ^d   Roli, Fabio ^b  

^a CITY UNIVERSITY OF HONG KONG   (Hong Kong)

^b UNIVERSITY OF CAGLIARI   (Italy)

^c UNIVERSITY OF SIENA   (Italy)

^d UNIVERSITY OF FLORENCE   (Italy)

Author keywords

Error correcting output codes; Fingerprint classification; Recursive neural networks; Support vector machines

Indexed keywords

IMAGING TECHNIQUES; NEURAL NETWORKS;

SUPPORT VECTOR MACHINES;

PATTERN RECOGNITION;

IMAGE CLASSIFICATION;

EID: 0036487278     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0031-3203(02)00039-0     Document Type: Article

References (37)

1. Fingerprint matching using transformation parameter clustering
2. A multichannel approach to fingerprint classification
3. Fingerprint classification by directional image partitioning
4. Fingerprint classification and recognition
5. Fingerprint classification
6. Fingerprint classification through self-organizing feature maps modified to treat uncertainty
7. Neural network based fingerprint classification
8. Fingerprint classification with neural networks
9. A hidden markov model fingerprint classifier
10. A syntactic approach to fingerprint pattern recognition
11. A structural approach to fingerprint classification
12. Combining fingerprint classifiers
13. Fingerprint classification by combination of at and structural approaches
14. A general framework for adaptive processing of data structures
15. Solving multiclass learning problems via error-correcting output codes
16. A tutorial on support vector machines for pattern recognition
17. Regularization networks and support vector machines
18. Large margin dags for multiclass classification
19. Support vector machines for 3-d object recognition
20. On the use of level curves in image analysis
21. Recursive distributed representations
22. Holographic reduced representations
23. Learning task-dependent distributed structure-representations by backpropagation through structure
24. Supervised neural networks for the classification of structures
25. Special section on connectionist models for learning in structured domains
26. Finding structure in time
27. Ensembles of neural networks for soft classification of remote sensing images
28. Combination of neural and statistical algorithms for supervised classification of remote-sensing images