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Expand Up @@ -6,27 +6,27 @@ Discover pretrained models for deep learning in MATLAB.

### Computer Vision
* [Image Classification](https://github.com/matlab-deep-learning/MATLAB-Deep-Learning-Model-Hub#image-classification-)
* [Object Detection](#ObjectDetection)
* [Semantic Segmentation](#SemanticSegmentation)
* [Instance Segmentation](#InstanceSegmentation)
* [Image Translation](#ImageTranslation)
* [Pose Estimation](#PoseEstimation)
* [Video Classification](#VideoClassification)
* [Text Detection & Recognition](#textdetection)
* [Object Detection](https://github.com/matlab-deep-learning/MATLAB-Deep-Learning-Model-Hub#object-detection-)
* [Semantic Segmentation](https://github.com/matlab-deep-learning/MATLAB-Deep-Learning-Model-Hub#semantic-segmentation-)
* [Instance Segmentation](https://github.com/matlab-deep-learning/MATLAB-Deep-Learning-Model-Hub#instance-segmentation-)
* [Image Translation](https://github.com/matlab-deep-learning/MATLAB-Deep-Learning-Model-Hub#image-translation-)
* [Pose Estimation](https://github.com/matlab-deep-learning/MATLAB-Deep-Learning-Model-Hub#pose-estimation-)
* [Video Classification](https://github.com/matlab-deep-learning/MATLAB-Deep-Learning-Model-Hub#video-classification-)
* [Text Detection & Recognition](https://github.com/matlab-deep-learning/MATLAB-Deep-Learning-Model-Hub#text-detection-and-recognition-)

### Natural Language Processing
* [Transformers](#transformers)
* [Transformers](https://github.com/matlab-deep-learning/MATLAB-Deep-Learning-Model-Hub#transformers-text-)

### Audio
* [Audio Embeddings](#AudioEmbeddings)
* [Audio Embeddings](https://github.com/matlab-deep-learning/MATLAB-Deep-Learning-Model-Hub#audio-embeddings-)
* [Sound Classification](#SoundClassification)
* [Pitch Estimation](#PitchEstimation)
* [Speech to Text](#Speech2Text)
* [Speech to Text](https://github.com/matlab-deep-learning/MATLAB-Deep-Learning-Model-Hub#speech-to-text-)

### Lidar
* [Point Cloud Classification](#PointCloud)
* [Point Cloud Segmentation](#PointCloudSeg)
* [Point Cloud Object Detection](#PointCloudObj)
* [Point Cloud Classification](https://github.com/matlab-deep-learning/MATLAB-Deep-Learning-Model-Hub#lidar-)
* [Point Cloud Segmentation](https://github.com/matlab-deep-learning/MATLAB-Deep-Learning-Model-Hub#lidar-)
* [Point Cloud Object Detection](https://github.com/matlab-deep-learning/MATLAB-Deep-Learning-Model-Hub#lidar-)

## Image Classification <a name="ImageClassification"/>

Expand Down Expand Up @@ -70,7 +70,7 @@ Pretrained networks have different characteristics that matter when choosing a n
![](Images/pretrained.png)
Figure. Comparing image classification model accuracy, speed and size.

[Back to top](#Models)
[Back to top](https://github.com/matlab-deep-learning/MATLAB-Deep-Learning-Model-Hub#matlab-deep-learning-model-hub)

## Object Detection <a name="ObjectDetection"/>

Expand Down Expand Up @@ -104,7 +104,7 @@ These networks have been trained to detect specific objects for a given applicat
| [Single Shot Detector (SSD)](https://www.mathworks.com/help/vision/ug/object-detection-using-single-shot-detector.html) | Vehicle detection | 44 |[Doc ](https://www.mathworks.com/help/vision/ug/object-detection-using-single-shot-detector.html)|<img src="Images/ObjectDetectionUsingSSD.png" width=150>|
| [Faster R-CNN](https://www.mathworks.com/help/vision/ug/object-detection-using-faster-r-cnn-deep-learning.html) | Vehicle detection | 118 |[Doc](https://www.mathworks.com/help/vision/ug/object-detection-using-faster-r-cnn-deep-learning.html)|<img src="Images/faster_rcnn.png" width=150>|

[Back to top](#Models)
[Back to top](https://github.com/matlab-deep-learning/MATLAB-Deep-Learning-Model-Hub#matlab-deep-learning-model-hub)

## Semantic Segmentation <a name="SemanticSegmentation"/>

Expand All @@ -127,7 +127,7 @@ This network has been trained to detect 20 objects classes from the PASCAL VOC d
| [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) |<img src="Images/adaptSeg.png" width=150>|


[Back to top](#Models)
[Back to top](https://github.com/matlab-deep-learning/MATLAB-Deep-Learning-Model-Hub#matlab-deep-learning-model-hub)

## Instance Segmentation <a name="InstanceSegmentation"/>

Expand All @@ -141,7 +141,7 @@ Inputs are RGB images, outputs are pixel classifications (semantic maps), boundi
| ------------- | ------------- |------------- |
| [Mask R-CNN](https://www.mathworks.com/help/vision/ref/maskrcnn.html) | 80 | [Doc](https://www.mathworks.com/help/vision/ref/maskrcnn.html) <br /> [Github](https://github.com/matlab-deep-learning/mask-rcnn)|

[Back to top](#Models)
[Back to top](https://github.com/matlab-deep-learning/MATLAB-Deep-Learning-Model-Hub#matlab-deep-learning-model-hub)

## Image Translation <a name="ImageTranslation"/>

Expand All @@ -159,7 +159,7 @@ Inputs are images, outputs are translated RGB images. This example workflow show
| [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) |<img src="Images/cyclegan_imagedenoising.png" width=150>|
| [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) |<img src="Images/SuperResolution.png" width=150>|

[Back to top](#Models)
[Back to top](https://github.com/matlab-deep-learning/MATLAB-Deep-Learning-Model-Hub#matlab-deep-learning-model-hub)

## Pose Estimation <a name="PoseEstimation"/>

Expand All @@ -173,7 +173,7 @@ All inputs are RGB images, outputs are heatmaps and part affinity fields (PAFs)
| ------------- | ------------- |------------- |
| [OpenPose](https://www.mathworks.com/help/deeplearning/ug/estimate-body-pose-using-deep-learning.html) | 14 | [Doc](https://www.mathworks.com/help/deeplearning/ug/estimate-body-pose-using-deep-learning.html) |

[Back to top](#Models)
[Back to top](https://github.com/matlab-deep-learning/MATLAB-Deep-Learning-Model-Hub#matlab-deep-learning-model-hub)

## Video Classification <a name="VideoClassification"/>

Expand All @@ -189,7 +189,7 @@ All inputs are Videos only or Video with Optical Flow data, outputs are gesture
| [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)
| [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)

[Back to top](#Models)
[Back to top](https://github.com/matlab-deep-learning/MATLAB-Deep-Learning-Model-Hub#matlab-deep-learning-model-hub)

## Text Detection and Recognition <a name="textdetection"/>

Expand All @@ -209,7 +209,7 @@ Inputs are RGB images, outputs are bounding boxes that identify regions of text.
| ------------- | ------------- |------------- |------------- |------------- |
| [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) |![](Images/7segment.png)|

[Back to top](#Models)
[Back to top](https://github.com/matlab-deep-learning/MATLAB-Deep-Learning-Model-Hub#matlab-deep-learning-model-hub)

## Transformers (Text) <a name="transformers"/>

Expand All @@ -231,7 +231,7 @@ Inputs are sequences of text, outputs are text feature embeddings.
| [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) |![](Images/finbert.png)|
| [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) |![](Images/gpt2.png)|

[Back to top](#Models)
[Back to top](https://github.com/matlab-deep-learning/MATLAB-Deep-Learning-Model-Hub#matlab-deep-learning-model-hub)

## Audio Embeddings <a name="AudioEmbeddings"/>

Expand Down Expand Up @@ -267,7 +267,7 @@ Inputs are Audio signals, outputs is text.
| [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) |
| [deepspeech](https://github.com/matlab-deep-learning/deepspeech) | Speech to Text | 167| 5.97 |[GitHub](https://github.com/matlab-deep-learning/deepspeech) |

[Back to top](#Models)
[Back to top](https://github.com/matlab-deep-learning/MATLAB-Deep-Learning-Model-Hub#matlab-deep-learning-model-hub)

## Lidar <a name="PointCloud"/>

Expand All @@ -287,7 +287,7 @@ Inputs are Lidar Point Clouds converted to five-channels, outputs are segmentati
| <a name="PointCloudObj"/>[PointPillars](https://www.mathworks.com/help/lidar/ug/object-detection-using-pointpillars-network.html) | Object Detection | 8| 3 |[Doc](https://www.mathworks.com/help/lidar/ug/object-detection-using-pointpillars-network.html)|
| [Complex YOLO v4](https://github.com/matlab-deep-learning/Lidar-object-detection-using-complex-yolov4) | Object Detection | 233 (complex-yolov4) <br /> 21 (tiny-complex-yolov4) | 3 |[GitHub](https://github.com/matlab-deep-learning/Lidar-object-detection-using-complex-yolov4)|

[Back to top](#Models)
[Back to top](https://github.com/matlab-deep-learning/MATLAB-Deep-Learning-Model-Hub#matlab-deep-learning-model-hub)

## Model requests
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).
Expand Down

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