American Sign Language Alphabet Recognition using Deep Learning
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arXiv
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| Hauptverfasser: | , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2019
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| _version_ | 1866929485117390848 |
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| author | Kasukurthi, Nikhil Rokad, Brij Bidani, Shiv Dennisan, Aju |
| author_facet | Kasukurthi, Nikhil Rokad, Brij Bidani, Shiv Dennisan, Aju |
| contents | Tremendous headway has been made in the field of 3D hand pose estimation but the 3D depth cameras are usually inaccessible. We propose a model to recognize American Sign Language alphabet from RGB images. Images for the training were resized and pre-processed before training the Deep Neural Network. The model was trained on a squeezenet architecture to make it capable of running on mobile devices with an accuracy of 83.29%. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_1905_05487 |
| institution | arXiv |
| publishDate | 2019 |
| record_format | arxiv |
| spellingShingle | American Sign Language Alphabet Recognition using Deep Learning Kasukurthi, Nikhil Rokad, Brij Bidani, Shiv Dennisan, Aju Computer Vision and Pattern Recognition Artificial Intelligence Tremendous headway has been made in the field of 3D hand pose estimation but the 3D depth cameras are usually inaccessible. We propose a model to recognize American Sign Language alphabet from RGB images. Images for the training were resized and pre-processed before training the Deep Neural Network. The model was trained on a squeezenet architecture to make it capable of running on mobile devices with an accuracy of 83.29%. |
| title | American Sign Language Alphabet Recognition using Deep Learning |
| topic | Computer Vision and Pattern Recognition Artificial Intelligence |
| url | https://arxiv.org/abs/1905.05487 |