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doc: extended set of supported applications and functionality
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tprimak committed Aug 14, 2018
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7 changes: 4 additions & 3 deletions README.md
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@@ -21,13 +21,14 @@ of the following deep learning topologies and variations of these.

| Application | Example topology
|:--- |:---
| Image recognition | AlexNet, VGG, GoogleNet, ResNet
| Image segmenation | FCN, SegNet
| Image recognition | AlexNet, VGG, GoogleNet, ResNet, MobileNet
| Image segmenation | FCN, SegNet, MaskRCNN, U-Net
| Volumetric segmentation | 3D-Unet
| Object detection | SSD, Faster R-CNN, Yolo
| Neural Machine Translation (experimental) | GNMT
| Speech Recognition (experimental) | DeepSpeech

| Adversarial Networks | DCGAN, 3DGAN
| Reinforcement Learning | A3C

Intel MKL-DNN is used in the following software products:
* [Caffe\* Optimized for Intel Architecture](https://github.com/intel/caffe)
4 changes: 2 additions & 2 deletions doc/mainpage.md
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@@ -19,7 +19,7 @@ The table below summarizes the list of supported functions and their variants.
| Primitive class | Primitive | fp32 training | fp32 inference | int8 inference |
| :---------------- | :----------------------- | :-----------: | :------------: | :------------: |
| Convolution | 2D direct convolution | x | x | x |
| | 2D direct deconvolution | x | x | |
| | 2D direct deconvolution | x | x | x |
| | 2D winograd convolution | x | x | x |
| | 3D direct convolution | x | x | |
| | 3D direct deconvolution | x | x | |
@@ -42,7 +42,7 @@ The table below summarizes the list of supported functions and their variants.
| | Bounded ReLU | | x | |
| | Soft ReLU | | x | |
| | Logistic regression | | x | |
| | Softmax | | x | |
| | Softmax | x | x | |
| Data manipulation | Reorder/quantization | x | x | x |
| | Sum | x | x | x |
| | Concat | x | x | x |

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