Titlebook: Computer Vision –ACCV 2016; 13th Asian Conferenc Shang-Hong Lai,Vincent Lepetit,Yoichi Sato Conference proceedings 2017 Springer Internatio

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離開真充足

https://doi.org/10.1007/978-3-030-69105-9employing bagging or boosting to train several diverse models. For large neural networks, however, this is prohibitively expensive. To address this issue, we propose a method to leverage the benefits of ensembles without explicitely training several expensive neural network models. In contrast to Dr

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巫婆

https://doi.org/10.1007/978-3-319-91418-3rsity allows robustness to distractors and resistance against over-fitting, two valuable attributes of a competent classification solution. Its data-driven nature is comparable to deep convolutional neural networks, which elegantly blend global and local information through progressively more specif