Deep Boosting of Diverse Experts

Wei Zhang, Qiuyu Chen, Jun Yu, Jianping Fan

Abstract:

In this paper, a deep boosting algorithm is developed to
learn more discriminative ensemble classifier by seamlessly combining a set of base deep CNNs (base experts)
with diverse capabilities, e.g., these base deep CNNs are
sequentially trained to recognize a set of
object classes in an easy-to-hard way according to their
learning complexities. Our experimental results have demonstrated
that our deep boosting algorithm can significantly improve the
accuracy rates on large-scale visual recognition.

TL;DR: A deep boosting algorithm is developed to learn more discriminative ensemble classifier by seamlessly combining a set of base deep CNNs.

Keywords: boosting learning, deep learning, neural network

Data: [CIFAR-100](https://paperswithcode.com/dataset/cifar-100)