most citedCommittees of deep feedforward networks trained with few data

4 citations · 7 across the 2 of their papers we have counts for

collaborators

2 papers

cs.CV2017★ 3 cited

Deep Convolutional Neural Networks as Generic Feature Extractors

Lars Hertel, Erhardt Barth, Thomas Käster +1

Recognizing objects in natural images is an intricate problem involving multiple conflicting objectives. Deep convolutional neural networks, trained on large datasets, achieve conv…

cs.CV2014★ 4 cited

Committees of deep feedforward networks trained with few data

Bogdan Miclut, Thomas Kaester, Thomas Martinetz +1

Deep convolutional neural networks are known to give good results on image classification tasks. In this paper we present a method to improve the classification result by combining…