Vitis AI

AI, Artificial Intelligence, computervision, Convolutional Neural Networks, datascience, deep learning, deeptech, embeddedvision, Neural Networks

14 September 2020

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Sign Language Recognition: Hand Object detection using R-CNN and YOLO

For our introduction to neural networks on FPGAs, we used a variation on the MNIST dataset made for sign language recognition. It keeps the same 28×28 greyscale image style used by the MNIST dataset released in 1999. As we noted in our previous article though, this dataset is very limiting and when trying to apply […]

AI, Artificial Intelligence, computervision, Convolutional Neural Networks, datascience, embedded, embeddedvision, MNIST, resolution, Vitis AI, xilinx

27 August 2020

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Improving Convolutional Neural Networks: The weaknesses of the MNIST based datasets and tips for improving poor datasets

Introduction In our previous tutorial series, we looked at sign language recognition using the sign language MNIST dataset based off the original 1999 MNIST dataset, which is considered the “Hello World” of machine learning. We did this because we wanted a practical example that could be trained on a standard CPU. The sign language MNIST […]

AI, Artificial Intelligence, computervision, Convolutional Neural Networks, fpga, Keras, TensorFlow, tutorial, vitis, Vitis AI, xilinx

14 August 2020

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Vitis AI using Tensorflow and Keras Tutorial Part 9

Part 9: Running our code on the DPU We now have our compiled model ready to run on our board. In this tutorial we will look at running our DPU and exploring the code that interacts with the DPU API. Introduction Getting Started Transforming Kaggle Data and Convolutional Neural Networks (CNNs) Training our Neural Network […]

AI, Artificial Intelligence, computervision, Convolutional Neural Networks, embeddedvision, fpga, Keras, Neural Networks, TensorFlow, vitis, Vitis AI, xilinx

5 August 2020

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Vitis AI using Tensorflow and Keras Tutorial Part 8

Part 8: Compiling our CNN We now have our complete model and must make it ready to be run on the FPGA. To do this, we must compile our model with the Vitis AI compiler which will convert and optimise our model into a format that is runnable on the DPU. This tutorial will focus […]

AI, Artificial Intelligence, computervision, Convolutional Neural Networks, deeptech, embeddedvision, fpga, Keras, machine learning, Neural Networks, TensorFlow, tutorial, vitis, Vitis AI, xilinx

1 August 2020

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Vitis AI using Tensorflow and Keras Tutorial Part 7

Part 7: Quantising our graph In our previous tutorial we produced our frozen model so now we can optimise it to make it run on our FPGA hardware efficiently, which we can do through quantisation. Quantisation is the process of reducing the number of bits used for our tensors and weights, but exactly why is […]

AI, Artificial Intelligence, computervision, Convolutional Neural Networks, deeptech, embeddedvision, fpga, Keras, machine learning, Neural Networks, TensorFlow, tutorial, vitis, Vitis AI, xilinx

23 July 2020

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Vitis AI using Tensorflow and Keras Tutorial part 6

Part 6: Converting and Freezing our CNN Now we have built a more optimal CNN by handling both under-fitting and over-fitting, we can begin the process of deploying our model on the FPGA itself. The first step in this process is to convert our Keras model to a TensorFlow model and then we need to […]

AI, Artificial Intelligence, Convolutional Neural Networks, deeptech, embedded, fpga, Keras, machine learning, Neural Networks, TensorFlow, tutorial, vitis, Vitis AI, xilinx

16 July 2020

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Vitis AI using Tensorflow and Keras Tutorial Part 5

Part 5: Optimising our CNN In our previous section, we both trained our network on a training set and tested it on a testing set and our accuracy on the training set (0.972) was higher than on our testing set (0.922). In an ideal design the training set should have the same accuracy as the […]

AI, Artificial Intelligence, computervision, Convolutional Neural Networks, deep learning, deeptech, embeddedvision, fpga, Keras, machine learning, TensorFlow, tutorial, vitis, Vitis AI, xilinx

10 July 2020

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Vitis AI using Tensorflow and Keras Tutorial part 4

Part 4: Training the neural network Welcome to Part 4 of our tutorial where we will be focused on training the neural network we built in the previous section Introduction Getting Started Transforming Kaggle Data and Convolutional Neural Networks (CNNs) Training our Neural Network (Current) Optimising our neural network Converting and Freezing our CNN Quanitising […]

Vitis AI using TensorFlow and Keras Tutorial Part 3

Part 3: Extracting Kaggle data and building the Convolutional Neural Network (CNN) Welcome to Part 3 of our tutorial where we will be focused on how to extract our data from the Kaggle set and building our Convolutional Neural Network. Introduction Getting Started Transforming Kaggle Data and Convolutional Neural Networks (CNNs) (Current) Training the neural […]

#embeddedsystems, AI, Artificial Intelligence, Convolutional Neural Networks, embedded, embeddedvision, fpga, Keras, TensorFlow, vitis, Vitis AI, xilinx

26 June 2020

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Vitis AI using TensorFlow and Keras Tutorial Part 2

Part 2: Introducing Sign Language MNIST Welcome to the second part in out tutorial in using Vitis AI with Tensorflow and Keras. Other parts of the tutorial can be found here: Introduction Getting Started (here) Transforming Kaggle Data and Convolutional Neural Networks (CNNs) Training the neural network Optimising our neural network Converting and Freezing our […]

Sign Language Recognition: Hand Object detection using R-CNN and YOLO

Improving Convolutional Neural Networks: The weaknesses of the MNIST based datasets and tips for improving poor datasets

Vitis AI using Tensorflow and Keras Tutorial Part 9

Vitis AI using Tensorflow and Keras Tutorial Part 8

Vitis AI using Tensorflow and Keras Tutorial Part 7

Vitis AI using Tensorflow and Keras Tutorial part 6

Vitis AI using Tensorflow and Keras Tutorial Part 5

Vitis AI using Tensorflow and Keras Tutorial part 4

Vitis AI using TensorFlow and Keras Tutorial Part 3

Vitis AI using TensorFlow and Keras Tutorial Part 2

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