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| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Venugopal Raskatla, Vijay Kumar | - |
| dc.date.accessioned | 2024-10-10T04:43:18Z | - |
| dc.date.available | 2024-10-10T04:43:18Z | - |
| dc.date.issued | 2021 | - |
| dc.identifier.uri | http://localhost:8080/xmlui/handle/123456789/1070 | - |
| dc.description.abstract | A deep learning assisted scheme for classification of noisy LG modes is proposed. This model is noise and alignment independent and will increase the accuracy and fidelity of OAM mode detection systems. | en_US |
| dc.description.sponsorship | NITW | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | Frontiers in Optics / Laser Science © Optica Publishing | en_US |
| dc.subject | Deep Learning | en_US |
| dc.subject | Assisted Classification | en_US |
| dc.subject | Noisy Laguerre | en_US |
| dc.subject | Gaussian Modes | en_US |
| dc.title | Deep Learning Assisted Classification of Noisy Laguerre Gaussian Modes | en_US |
| dc.type | Other | en_US |
| Appears in Collections: | Physics | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| FiO-2021-JTu1A.16.pdf | 536.24 kB | Adobe PDF | View/Open |
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