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Capsule-Based Persian/Arabic Robust Handwritten Digit Recognition Using EM Routing

2019-12-08 · Ali Ghofrani, Rahil Mahdian Toroghi

In this paper, the problem of handwritten digit recognition has been addressed. However, the underlying language is Persian/Arabic, and the system with which this task is a capsule network (CapsNet) has recently emerged as a more advanced architecture than its ancestor, namely CNN (Convolutional Neural Network). The training of the architecture is performed using the Hoda dataset, which has been provided for Persian/Arabic handwritten digits. The output of the system clearly outperforms the results achieved by its ancestors, as well as other previously presented recognition algorithms.

📄 PDF Abstract BibTeX arXiv:1912.03634

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Tasks

Handwritten Digit Recognition

Methods 이 논문이 사용한 방법론

Capsule Network A capsule is an activation vector that basically executes on its inputs some complex internal computations. Length of these activation vectors signifies the probability of…

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