Dflat Tensorflow
(Tensorflow Version) D-Flat is a forward and inverse design framework for flat optics. Although specially geared for the design of metasurface optics, it may be used for any end-to-end imaging and sensing task.
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Automatic_speech_recognition | 2,743 | 2 years ago | 69 | mit | Python | |||||
| End-to-end Automatic Speech Recognition for Madarian and English in Tensorflow | ||||||||||
| Tensorflow_end2end_speech_recognition | 275 | 6 years ago | 11 | mit | Python | |||||
| End-to-End speech recognition implementation base on TensorFlow (CTC, Attention, and MTL training) | ||||||||||
| Neuraldialog Cvae | 261 | 5 years ago | 4 | apache-2.0 | OpenEdge ABL | |||||
| Tensorflow Implementation of Knowledge-Guided CVAE for dialog generation ACL 2017. It is released by Tiancheng Zhao (Tony) from Dialog Research Center, LTI, CMU | ||||||||||
| Dflat Tensorflow | 68 | 4 months ago | 2 | gpl-3.0 | Python | |||||
| (Tensorflow Version) D-Flat is a forward and inverse design framework for flat optics. Although specially geared for the design of metasurface optics, it may be used for any end-to-end imaging and sensing task. | ||||||||||
| Speech Transformer Tf2.0 | 51 | 5 years ago | Python | |||||||
| transformer for ASR-systerm (via tensorflow2.0) | ||||||||||
| End2endasr | 43 | 6 years ago | 5 | Python | ||||||
| implement end-to-end asr algorithm with tensorflow | ||||||||||
| Speech Recognition | 18 | 6 years ago | 2 | mit | Python | |||||
| End-to-end Automatic Speech Recognition for Madarian and English in Tensorflow | ||||||||||
| Video Streamer | 10 | 6 months ago | apache-2.0 | Python | ||||||
| The repository contains a reference end-to-end pipeline for a real-time video analytics application. Realtime data is provided to an inference endpoint that executes single shot object detection. The metadata created during inference is then uploaded to a database for curation. | ||||||||||
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