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@@ -127,7 +127,7 @@ This network has been trained to detect 20 objects classes from the PASCAL VOC d
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|[AdaptSeg (GAN)](https://www.mathworks.com/help/deeplearning/ug/train-deep-learning-semantic-segmentation-network-using-3d-simulation-data.html)| Model tuning using 3-D simulation data | 54.4 |[Doc](https://www.mathworks.com/help/deeplearning/ug/train-deep-learning-semantic-segmentation-network-using-3d-simulation-data.html)|<imgsrc="Images/adaptSeg.png"width=150>|
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## Image Translation <aname="ImageTranslation"/>
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|[CycleGAN](https://www.mathworks.com/help/images/unsupervised-medical-image-denoising-using-cyclegan.html)| Medical Image Denoising | 75.3 |[Doc](https://www.mathworks.com/help/images/unsupervised-medical-image-denoising-using-cyclegan.html)|<imgsrc="Images/cyclegan_imagedenoising.png"width=150>|
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|[VDSR](https://www.mathworks.com/help/images/single-image-super-resolution-using-deep-learning.html)| Super Resolution (estimate a high-resolution image from a low-resolution image) | 2.4 |[Doc](https://www.mathworks.com/help/images/single-image-super-resolution-using-deep-learning.html)|<imgsrc="Images/SuperResolution.png"width=150>|
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## Pose Estimation <aname="PoseEstimation"/>
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## Video Classification <aname="VideoClassification"/>
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| [R(2+1)D](https://www.mathworks.com/help/vision/ref/r2plus1dvideoclassifier.html) | Video | 112 |400 |Faster convergence than Inflated-3D|[Doc](https://www.mathworks.com/help/vision/ref/r2plus1dvideoclassifier.html)
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| [Inflated-3D](https://www.mathworks.com/help/vision/ref/inflated3dvideoclassifier.html) | Video & Optical Flow data | 91 | 400 |Accuracy of the classifier improves when combining optical flow and RGB data.| [Doc](https://www.mathworks.com/help/vision/ref/inflated3dvideoclassifier.html)
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## Text Detection and Recognition <aname="textdetection"/>
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|[Seven Segment Digit Recognition](https://github.com/matlab-deep-learning/Seven-Segment-Digit-Recognition)|Seven segment digit recognition using deep learning and OCR. This is helpful in industrial automation applications where digital displays are often surrounded with complex background. | 3.8 |[GitHub](https://github.com/matlab-deep-learning/Seven-Segment-Digit-Recognition)||
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## Transformers (Text) <aname="transformers"/>
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|[FinBERT](https://github.com/matlab-deep-learning/transformer-models#bert-and-finbert)| The FinBERT model is a BERT model for financial sentiment analysis | 388 |[GitHub](https://github.com/matlab-deep-learning/transformer-models#bert-and-finbert)||
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|[GPT-2](https://github.com/matlab-deep-learning/transformer-models#gpt-2)| The GPT-2 model is a decoder model used for text summarization.| 1.2GB |[GitHub](https://github.com/matlab-deep-learning/transformer-models#gpt-2)||
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## Audio Embeddings <aname="AudioEmbeddings"/>
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|[wav2vec](https://github.com/matlab-deep-learning/wav2vec-2.0)| Speech to Text | 236| 3.2 |[GitHub](https://github.com/matlab-deep-learning/wav2vec-2.0)|
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|[deepspeech](https://github.com/matlab-deep-learning/deepspeech)| Speech to Text | 167| 5.97 |[GitHub](https://github.com/matlab-deep-learning/deepspeech)|
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## Lidar <aname="PointCloud"/>
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## Model requests
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If you'd like to request MATLAB support for additional pretrained models, [**please create an issue from this repo**](https://docs.github.com/en/issues/tracking-your-work-with-issues/creating-an-issue).
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