Pairwise Confusion for Fine-Grained Visual Classification
Pairwise Confusion for Fine-Grained Visual Classification 摘要 文中主要介绍了一种称为pairwise confusion正则化的方法。这类方法能够关注到类内的相似性。 在pairwise confusion结构中，使用了孪生网络在一个新的loss function中训练，目的是为了将类别内的概率更加接近。 网络结构 使用一个类
相关文章
- 1. Pairwise Confusion for Fine-Grained Visual Classification 阅读笔记
- 2. Learning Attentive Pairwise Interaction for Fine-Grained Classification论文解读
- 3. CNNs for Text Classification
- 4. Linear Models for Classification
- 5. Understanding Confusion Matrix
- 6. 论文笔记: (compact) Bilinear Pooling, Confusion
- 7. [Bayes] Maximum Likelihood estimates for text classification
- 8. Confusion Matrix-混淆矩阵
- 9. View Confusion Feature Learning for Person Re-identification
- 10. 《Character-level Convolutional Networks for Text Classification》
- 更多相关文章...
- • Swift for 循环 - Swift 教程
- • Scala for循环 - Scala教程
- • PHP开发工具
- • C# 中 foreach 遍历的用法
相关标签/搜索
每日一句
-
每一个你不满意的现在，都有一个你没有努力的曾经。
欢迎关注本站公众号,获取更多信息
相关文章
- 1. Pairwise Confusion for Fine-Grained Visual Classification 阅读笔记
- 2. Learning Attentive Pairwise Interaction for Fine-Grained Classification论文解读
- 3. CNNs for Text Classification
- 4. Linear Models for Classification
- 5. Understanding Confusion Matrix
- 6. 论文笔记: (compact) Bilinear Pooling, Confusion
- 7. [Bayes] Maximum Likelihood estimates for text classification
- 8. Confusion Matrix-混淆矩阵
- 9. View Confusion Feature Learning for Person Re-identification
- 10. 《Character-level Convolutional Networks for Text Classification》