Dense Classification and Implanting for Few-Shot Learning论文笔记
论文地址:https://arxiv.org/pdf/1903.05050.pdf 摘要 基于较少的训练数据对神经网络进行训练一直是一个比较困难的问题，本篇论文设计了一种将较大的数据集中中学习到的知识迁移到较小的数据集的方法来完成小样本学习任务。论文主要的创新点如下： 设计了一种基于特征图的密集分类器，首次探索了局部信息在小样本学习中的作用。 迁移，具体表现为在预训练好的模型之上增添新的神经元进行
相关文章
- 1. 论文阅读笔记《Dense Classification and Implanting for Few-Shot Learning》
- 2. 论文阅读笔记《Deep Active Learning for Civil Infrastructure Defect Detection and Classification》
- 3. PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation 论文笔记
- 4. 【论文阅读笔记】MULTI-SCALE DENSE NETWORKS FOR RESOURCE EFFICIENT IMAGE CLASSIFICATION
- 5. Focal Loss for Dense Object Detection论文笔记
- 6. 【Active Learning - 01】 2013_CVPR_Adaptive Active Learning for Image Classification 论文笔记
- 7. Learning a Deep ConvNet for Multi-label Classification with Partial Labels 论文笔记
- 8. [论文笔记]Focal Loss for Dense Object Detection
- 9. 论文笔记：Focal Loss for Dense Object
- 10. 论文笔记--Automatic Bus Planner for Dense PCBs
- 更多相关文章...
- • ASP.NET Razor - 标记 - ASP.NET 教程
- • Scala for循环 - Scala教程
- • Tomcat学习笔记（史上最全tomcat学习笔记）
- • RxJava操作符（七）Conditional and Boolean
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。
最新文章
欢迎关注本站公众号,获取更多信息
相关文章
- 1. 论文阅读笔记《Dense Classification and Implanting for Few-Shot Learning》
- 2. 论文阅读笔记《Deep Active Learning for Civil Infrastructure Defect Detection and Classification》
- 3. PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation 论文笔记
- 4. 【论文阅读笔记】MULTI-SCALE DENSE NETWORKS FOR RESOURCE EFFICIENT IMAGE CLASSIFICATION
- 5. Focal Loss for Dense Object Detection论文笔记
- 6. 【Active Learning - 01】 2013_CVPR_Adaptive Active Learning for Image Classification 论文笔记
- 7. Learning a Deep ConvNet for Multi-label Classification with Partial Labels 论文笔记
- 8. [论文笔记]Focal Loss for Dense Object Detection
- 9. 论文笔记：Focal Loss for Dense Object
- 10. 论文笔记--Automatic Bus Planner for Dense PCBs