Skip to content

Commit

Permalink
Update README.md
Browse files Browse the repository at this point in the history
  • Loading branch information
AdamMiltonBarker committed May 4, 2021
1 parent 3e34002 commit da4d6e7
Showing 1 changed file with 5 additions and 4 deletions.
9 changes: 5 additions & 4 deletions README.md
Original file line number Diff line number Diff line change
Expand Up @@ -23,7 +23,7 @@
- [Intel® Distribution of OpenVINO™ Toolkit](#intel-distribution-of-openvino-toolkit)
- [Intel® Movidius™ Neural Compute Stick 2](#intel-movidius-neural-compute-stick-2)
- [Acute Lymphoblastic Leukemia oneAPI Classifier 2021](#acute-lymphoblastic-leukemia-oneapi-classifier-2021)
- [GETTING STARTED](#getting-started)
- [GETTING STARTED](#getting-started)
- [Contributing](#contributing)
- [Contributors](#contributors)
- [Versioning](#versioning)
Expand Down Expand Up @@ -100,10 +100,9 @@ Source: [Acute Lymphoblastic Leukemia Tensorflow Classifier 2020](https://github
[Intel® Optimization for TensorFlow](https://software.intel.com/content/www/us/en/develop/articles/intel-optimization-for-tensorflow-installation-guide.html) optimizes the popular Tensorflow framework using Intel® Math Kernel Library for Deep Neural Networks (Intel® MKL-DNN). Intel® MKL-DNN is an open-source library for enhancing performance by accelerating deep learning libraries such as Tensorflow on Intel architecture.

## Intel® Distribution of OpenVINO™ Toolkit
[Intel® Distribution of OpenVINO™ Toolkit](https://software.intel.com/content/www/us/en/develop/tools/openvino-toolkit.html) is based on Convolutional Neural Networks and optimizes models used on Intel CPUs/GPUs, VPUs, FPGA etc. Models are converted to [Interassetste Representations (IR)](https://docs.openvinotoolkit.org/latest/openvino_docs_MO_DG_IR_and_opsets.html) which allow them to be used with the [Inference Engine](https://docs.openvinotoolkit.org/2020.2/_docs_IE_DG_Deep_Learning_Inference_Engine_DevGuide.html).
[Intel® Distribution of OpenVINO™ Toolkit](https://software.intel.com/content/www/us/en/develop/tools/openvino-toolkit.html) is based on Convolutional Neural Networks and optimizes models used on Intel CPUs/GPUs, VPUs, FPGA etc. Models are converted to [Intermediate Representations (IR)](https://docs.openvinotoolkit.org/latest/openvino_docs_MO_DG_IR_and_opsets.html) which allow them to be used with the [Inference Engine](https://docs.openvinotoolkit.org/2020.2/_docs_IE_DG_Deep_Learning_Inference_Engine_DevGuide.html).

## Intel® Movidius™ Neural Compute Stick 2
(https://software.intel.com/content/www/us/en/develop/hardware/neural-compute-stick.html)
The [Intel® Movidius™ Neural Compute Stick 2](https://software.intel.com/content/www/us/en/develop/hardware/neural-compute-stick.html) is a USB plug & play AI device for deep learning inference at the edge. Combined with the Intel® OpenVINO™ Toolkit, developers can develop, fine-tune, and deploy convolutional neural networks (CNNs) on low-power applications that require real-time inference.

 
Expand All @@ -122,7 +121,9 @@ To create the newly improved **Acute Lymphoblastic Leukemia oneAPI Classifier 20

- Test the model using commandline and classify unseen data using HTTP requests to a local API endpoint and via the HIAS network.

## GETTING STARTED
 

# GETTING STARTED

Ready to get started ? Head over to the [Getting Started guide](documentation/getting-started.md) for instructions on how to download/install and setup the Acute Lymphoblastic Leukemia oneAPI Classifier 2021.

Expand Down

0 comments on commit da4d6e7

Please sign in to comment.