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Off-line Signature Verification Using HMM for Random, Simple and Skilled Forgeries.

, , and . ICDAR, page 1031-1034. IEEE Computer Society, (2001)

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Combining Diversity and Classification Accuracy for Ensemble Selection in Random Subspaces., , and . IJCNN, page 2144-2151. IEEE, (2006)Contribution of data complexity features on dynamic classifier selection., , , , and . IJCNN, page 4396-4403. IEEE, (2016)Adapting dynamic classifier selection for concept drift., , , and . Expert Syst. Appl., (2018)DESlib: A Dynamic ensemble selection library in Python., , , and . CoRR, (2018)FIRE-DES++: Enhanced Online Pruning of Base Classifiers for Dynamic Ensemble Selection., , , and . CoRR, (2018)Analyzing features learned for Offline Signature Verification using Deep CNNs., , and . ICPR, page 2989-2994. IEEE, (2016)Meta-regression based pool size prediction scheme for dynamic selection of classifiers., , , and . ICPR, page 216-221. IEEE, (2016)Fast two-level Viterbi search algorithm for unconstrained handwriting recognition., , and . ICASSP, page 3537-3540. IEEE, (2002)A neural network approach to off-line signature verification using directional PDF., , and . Pattern Recognit., 29 (3): 415-424 (1996)Learning features for offline handwritten signature verification using deep convolutional neural networks., , and . Pattern Recognit., (2017)