Deep Boosting of Diverse ExpertsDownload PDF

15 Feb 2018, 21:29 (modified: 10 Feb 2022, 11:38)ICLR 2018 Conference Blind SubmissionReaders: Everyone
Keywords: boosting learning, deep learning, neural network
TL;DR: A deep boosting algorithm is developed to learn more discriminative ensemble classifier by seamlessly combining a set of base deep CNNs.
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.
Data: [CIFAR-100](https://paperswithcode.com/dataset/cifar-100)
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