Complete Vitis AI tutorial with TensorFlow, Keras ...

Part 1: Introduction Welcome to our multi part tutorial on using Vitis AI with TensorFlow, Keras and BeetleboxCI. This tutorial series is designed to teach the entire development process from initial code to forming an entire Continuous Integration pipeline that

Why use Continuous Integration for FPGA design?

FPGA design has long been using traditional hardware development practises such as waterfall and V-model, but we believe the future of FPGAs lies in continuous integration and in this video we explore why. Transcript: FPGA design development has always embraced

Sign Language Recognition: Hand Object detection u...

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

Getting started with Computer Vision for Vitis 202...

Welcome to the 2020.1 version of getting started with computer vision on Vitis on Zynq. The release of 2020.1 saw significant changes from the old 2019.2 version and we thought it would be useful to update this tutorial to reflect

Getting started with Computer Vision for Vitis 202...

Welcome to the 2020.1 version of getting started with computer vision on Vitis on Zynq. The release of 2020.1 saw significant changes from the old 2019.2 version and we thought it would be useful to update this tutorial to reflect

Vitis AI using Tensorflow and Keras Tutorial Part ...

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

Vitis AI using Tensorflow and Keras Tutorial part ...

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

Vitis AI using Tensorflow and Keras Tutorial Part ...

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

Vitis AI using Tensorflow and Keras Tutorial part ...

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)

Sign Language Machine Learning
Vitis AI using TensorFlow and Keras Tutorial Part ...

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.

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