New design strategies of deep heterogenous convolutional neural networks ensembles for breast cancer diagnosis

Results showed the effectiveness of deep end-to-end ensemble learning techniques for histopathological breast cancer images classification since the ensembles designed using weighted voting with the selection by accuracy strategy method exceeded the ones designed using the selection by diversity or by accuracy and diversity strategies.