Deep Learning with OBH for Real-Time Rotation-Invariant Signs Detection-Reference-Cited by-同舟云学术

Deep Learning with OBH for Real-Time Rotation-Invariant Signs Detection

Published:2023-02-23 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2023 12th International Conference on Software and Computer Applications
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Author:

Akhter Shamim¹^ORCID,Quaderi Shah Jafor Sadeek²^ORCID,Ahmed Saleh Ud-Din¹^ORCID

Affiliation:

1. AISIP Labroratory, Department of Computer Science and Engineering, Ahsanullah University of Science and Technology(AUST), Bangladesh

2. Department of Computer Science and Engineering, Asian University of Bangladesh(AUB), Bangladesh

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3587828.3587884

Reference22 articles.

1. S. U. d. Ahmad and S. Akhter , " Real time rotation invariant static hand gesture recognition using an orientation based hash code" in 2013 International Conference on Informatics , Electronics and Vision (ICIEV) , Dhaka , 2013 , pp. 1 - 6 . S. U. d. Ahmad and S. Akhter, "Real time rotation invariant static hand gesture recognition using an orientation based hash code" in 2013 International Conference on Informatics, Electronics and Vision (ICIEV), Dhaka, 2013, pp. 1-6.

2. American Sign Language Character Recognition Using Convolution Neural Network

3. A mobile application of American sign language translation via image processing algorithms

4. C. Dong , M. C. Leu , and Z. Yin , “ American sign language alphabet recognition using microsoft kinect ” in Proceedings of the IEEE conference on computer vision and pattern recognition workshops (pp. 44-52) , 2015 . C. Dong, M. C. Leu, and Z. Yin, “American sign language alphabet recognition using microsoft kinect” in Proceedings of the IEEE conference on computer vision and pattern recognition workshops (pp. 44-52), 2015.

5. Classification of Satellite Images through Gabor Filter using SVM