OverFeat: Integrated Recognition, Localization and Detection using Convolutional Networks
这篇文章将classfication，localization和detection三种任务同时用一个CNN网络进行实现。并且提出了一个十分厉害的feature extractor：Overfeat。 在ImageNet数据集中，物体在图片中呈现的位置大致是在图片的中间，而且占据了图片很大的地方，但是感兴趣的物体分布却非常的不同。常用的解决方案有3种：1. 将CNN用在图片的不同位置，或者使用多尺寸
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相关文章
- 1. OverFeat: Integrated Recognition, Localization and Detection using Convolutional Networks
- 2. 【OverFeat】《OverFeat：Integrated Recognition, Localization and Detection using Convolutional Networks》
- 3. OverFeat: Integrated Recognition, Localization and Detection using Convolutional Networks 论文笔记
- 4. OverFeat: Integrated Recognition, Localization and Detection using Convolutional Networks总结
- 5. 对 OverFeat: Integrated Recognition, Localization and Detection using Convolutional Networks 一文的理解...
- 6. OverFeat: Integrated Recognition, Localization and Detection using Convolutional Networks论文阅读笔记
- 7. 论文笔记：OverFeat: Integrated Recognition, Localization and Detection using Convolutional Networks
- 8. RCNN学习笔记(8):OverFeat:Integrated Recognition, Localization and Detection using Convolutional Network
- 9. Emotion Recognition Using Graph Convolutional Networks
- 10. 论文笔记1.3——Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks