Towards Interpreting Robotic System for Fingerspelling Recognition in Real Time-Reference-Cited by-同舟云学术

Towards Interpreting Robotic System for Fingerspelling Recognition in Real Time

Published:2018-03 Issue: Volume: Page:
ISSN:
Container-title:Companion of the 2018 ACM/IEEE International Conference on Human-Robot Interaction
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Author:

Kalidolda Nazerke¹,Sandygulova Anara¹

Affiliation:

1. Nazarbayev University, Astana, Kazakhstan

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3173386.3177085

Reference8 articles.

1. Mart'ın Abadi Ashish Agarwal Paul Barham Eugene Brevdo Zhifeng Chen Craig Citro Greg S Corrado Andy Davis Jeffrey Dean Matthieu Devin et almbox. . 2016. Tensorflow: Large-scale machine learning on heterogeneous distributed systems. arXiv preprint arXiv:1603.04467 (2016). Mart'ın Abadi Ashish Agarwal Paul Barham Eugene Brevdo Zhifeng Chen Craig Citro Greg S Corrado Andy Davis Jeffrey Dean Matthieu Devin et almbox. . 2016. Tensorflow: Large-scale machine learning on heterogeneous distributed systems. arXiv preprint arXiv:1603.04467 (2016).

2. Franccois Chollet et almbox. . 2015. Keras. (2015). Franccois Chollet et almbox. . 2015. Keras. (2015).

3. German Ignacio Parisi Pablo Barros and Stefan Wermter . 2014. FINGeR: Framework for interactive neural-based gesture recognition. ESANN. German Ignacio Parisi Pablo Barros and Stefan Wermter . 2014. FINGeR: Framework for interactive neural-based gesture recognition. ESANN.

4. Lionel Pigou Sander Dieleman Pieter-Jan Kindermans and Benjamin Schrauwen . 2014. Sign language recognition using convolutional neural networks Workshop at the European Conference on Computer Vision. Springer 572--578. Lionel Pigou Sander Dieleman Pieter-Jan Kindermans and Benjamin Schrauwen . 2014. Sign language recognition using convolutional neural networks Workshop at the European Conference on Computer Vision. Springer 572--578.

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