As long as certain key features of an object are present in the test data, CNN's classify the test data as the object, disregarding features' relative spatial orientation to each other. This causes false positives. The lack of rotational invariance in CNN's would cause the network to ...
[10] E. Xi, S. Bing, and Y. Jin, ``Capsule network performance on complex data,'' Dec. 2017, arXiv:1712.03480v1. [Online]. Available:https://arxiv.org/abs/1712.03480v1 [11] D. Wang and Q. Liu, ``An optimization view on dynamic routing between capsules,'' presented at the 6t...
[10] E. Xi, S. Bing, and Y. Jin, ``Capsule network performance on complex data,'' Dec. 2017, arXiv:1712.03480v1. [Online]. Available:https://arxiv.org/abs/1712.03480v1 [11] D. Wang and Q. Liu, ``An optimization view on dynamic routing between capsules,'' presented at the 6t...
However, CapsNet gets a poor performance on more complex datasets like CIFAR-10. To address this problem, we focus on the improvement of the original CapsNet from both the network structure and the dynamic routing mechanism. A new CapsNet architecture aiming at complex data called Capsule Network...
Xi, E., Bing, S. & Jin, Y. Capsule network performance on complex data.arXiv:1712.03480(arXiv preprint) (2017). Wang, D. & Liu, Q. An optimization view on dynamic routing between capsules (2018). Lenssen, J. E., Fey, M. & Libuschewski, P. Group equivariant capsule networks....
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] (...
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. ...
Capsule Network Performance on Complex Data In recent years, convolutional neural networks (CNN) have played an important role in the field of deep learning. Variants of CNN's have proven to be very successful in classification tasks across different domains. However, there are tw... E Xi,S ...
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