Large-Margin Softmax Loss for Convolutional Neural Networks
Large-Margin Softmax Loss for Convolutional Neural Networks 在本文中，我們將軟最大損耗定義爲交叉熵損耗、軟最大函數和最後一個完全連接層的組合（見圖1）。在這種定義下，許多流行的CNN模型可以被視爲卷積特徵學習組件和softmax損失組件的組合，如圖1所示。 儘管它的流行，當前的軟最大損失並不明確鼓勵類內的緊密性和類間的可分離性。 我們的主
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相關文章
- 1. Large-Margin Softmax Loss for Convolutional Neural Networks
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- 3. 論文筆記 | Large-Margin Softmax Loss for Convolutional Neural Networks
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- 5. Convolutional Neural Networks: Application
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- 9. 《Convolutional Neural Networks for Sentence Classification》
- 10. Recurrent Convolutional Neural Networks for Text Classification