Jin, ``Capsule network performance on complex data,'' Dec. 2017, arXiv:1712.03480v1. [Online]. Available: arxiv.org/abs/1712.0348 [11] D. Wang and Q. Liu, ``An optimization view on dynamic routing between capsu
However, this network architecture is built specifically for MNIST and gets a poor performance on more complex datasets like CIFAR-10. To address this problem, aiming at complex data, we propose a new CapsNet architecture called Fractionally-Strided Convolutional Capsule Network (FSC-CapsNet). We ...
Overall, the first convolutional part of the network can be modelled as a single function\(H_{Conv}\)that maps the input image onto a higher dimensional space that facilitates the capsule creation. On the other hand, the second part of the network is the main instrument used by primary ca...
Capsule Network Performance on Complex Data - Xi, E., Bing, S. and Jin, Y. (2017) Accurate reconstruction of image stimuli from human fMRI based on the decoding model with capsule network architecture - Qiao, K., Zhang, C., Wang, L., Yan, B., Chen, J., Zeng, L. and Tong, L...
Xi E, Bing S, Jin Y (2017) Capsule network performance on complex data. arXiv preprint arXiv:1712.03480 Xiang C, Zhang L, Tang Y, Zou W, Xu C (2018) Ms-capsnet: a novel multi-scale capsule network. IEEE Signal Process Lett 25(12):1850–1854 Article Google Scholar Zagoruyko S,...
为什么Capsule Network在Cifar数据集上表现不好？可参考《Capsule Network Performance on Complex Data》，...
on comparatively lesser number of data points with a better performance in solving the same problem. Researchers have developed a state of the art performance of Capsule Networks on the ultra-popular MNIST dataset with a couple of hundred times less data. This is the power of Capsule network. ...
Jin Capsule Network Performance on Complex Data arXiv1712.03480v1 [stat.ML] (2017), pp. 1-7 View in ScopusGoogle Scholar Xia et al., 2018 C. Xia, C. Zhang, X. Yan, Y. Chang, P.S. Yu Zero-shot User Intent Detection via Capsule Neural Networks metharXiv 1809.00385v1 [cs.CL] (...
By adding two layers of attention mechanisms, the neural network can pay more attention to the information. The more CapsNet understands the entity characteristics of the image, the better its performance in the classification task. Conclusion In this paper, our team proposed a CapsNet based on a...
capsule输出一个向量,并且可以选择将信息传送到上层的那个capsule。对于每个潜在的parent,capsule network可以增加或者降低连接强度。这种routing by agreement机制在添加方差方面比max-pooling更加有效。 Reconstruction Regularization 传统CNN使用dropout避免过拟合,而Capsule通过重构自动编码器来达到同样的目的。在训练时,除了正确...