Domain Adaptive Neural Networks for Object Recognition
本篇是迁移学习专栏介绍的第五篇论文，PRICAI 2014的DaNN（Domain Adaptive Neural Network）。 Abstract 提出了一种简单的神经网络模型来处理目标识别中的Domain Adaptive问题。我们的模型将Maximum Mean Discrepancy(MMD)作为正则化方法引入监督学习中，以减少潜在空间中源域和目标域的分布不匹配。从实验中，我们证明MM
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相关文章
- 1. CS231n Convolutional Neural Networks for Visual Recognition
- 2. Convolutional Neural Networks for Speech Recognition///2014
- 3. Convolutional Neural Networks for Visual Recognition
- 4. View Adaptive Neural Networks for High Performance Skeleton-based Human Action Recognition
- 5. Exploring Categorical Regularization for Domain Adaptive Object Detection
- 6. Deep Neural Networks for Object Detection
- 7. Adaptive Graph Convolutional Neural Networks
- 8. 论文：3D Convolutional Neural Networks for Human Action Recognition
- 9. 【One Shot】《Siamese Neural Networks for One-shot Image Recognition》
- 10. Domain Adaptation for Object Recognition: An Unsupervised Approach