14 Sep
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 in our previous article though, this dataset is very limiting
27 Aug
Improving Convolutional Neural Networks: The weakn...
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
14 Aug
Vitis AI using Tensorflow and Keras Tutorial Part ...
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
05 Aug
Vitis AI using Tensorflow and Keras Tutorial Part ...
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
01 Aug
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 reducing the number of bits used for our tensors and
23 Jul
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 is to convert our Keras model to a TensorFlow model
16 Jul
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 (0.922). In an ideal design the training set should have
10 Jul
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) Training our Neural Network (Current) Optimising our neural network Converting
02 Jul
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. Introduction Getting Started Transforming Kaggle Data and Convolutional Neural Networks
26 Jun
Vitis AI using TensorFlow and Keras Tutorial Part ...
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
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