161 citations · 268 across the 13 of their papers we have counts for
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cs.CV2015★ 3 cited
Deep Boosting: Joint Feature Selection and Analysis Dictionary Learning in Hierarchy
Zhanglin Peng, Ya Li, Zhaoquan Cai +1
This work investigates how the traditional image classification pipelines can be extended into a deep architecture, inspired by recent successes of deep neural networks. We propose…
cs.CV2015★ 4 cited
Deep Boosting: Layered Feature Mining for General Image Classification
Zhanglin Peng, Liang Lin, Ruimao Zhang +1
Constructing effective representations is a critical but challenging problem in multimedia understanding. The traditional handcraft features often rely on domain knowledge, limitin…