Restricted Boltzmann machines based oversampling and semi-supervised learning for false positive reduction in breast CAD
نویسندگان
چکیده
منابع مشابه
Restricted Boltzmann machines based oversampling and semi-supervised learning for false positive reduction in breast CAD.
The false-positive reduction (FPR) is a crucial step in the computer aided detection system for the breast. The issues of imbalanced data distribution and the limitation of labeled samples complicate the classification procedure. To overcome these challenges, we propose oversampling and semi-supervised learning methods based on the restricted Boltzmann machines (RBMs) to solve the classificatio...
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ژورنال
عنوان ژورنال: Bio-Medical Materials and Engineering
سال: 2015
ISSN: 1878-3619,0959-2989
DOI: 10.3233/bme-151453