@book{
 title = {An efficient way of combining SVMs for handwritten digit recognition},
 type = {book},
 year = {2012},
 source = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
 keywords = {handwriting digit classifier,pattern recognition,support vector machine},
 volume = {7553 LNCS},
 issue = {PART 2},
 id = {c0dc3f0e-e52a-340a-9509-7619234c23d6},
 created = {2019-02-14T18:02:00.995Z},
 file_attached = {false},
 profile_id = {74e7d4ea-3dac-3118-aab9-511a5b337e8f},
 last_modified = {2019-02-14T18:02:00.995Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {This paper presents a method of combining SVMs (support vector machines) for multiclass problems that ensures a high recognition rate and a short processing time when compared to other classifiers. This hierarchical SVM combination considers the high recognition rate and short processing time as evaluation criteria. The used case study was the handwritten digit recognition problem with promising results. © 2012 Springer-Verlag.},
 bibtype = {book},
 author = {Neves, R.F.P. and Zanchettin, C. and Filho, A.N.G.L.},
 doi = {10.1007/978-3-642-33266-1_29}
}

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