![]() ![]() MNIST(RT_Deployment) project - deployment of pretrained model on NI's Real Time targets.Ħ. MNIST_Classifier(Deploy).vi - deploying pretrained network by automatically loading network configuration and weights files generated from the examples above.ĥ. MNIST_Classifier_CNN(Train).vi - training the deep neural network for image classification task in handwritten digit recognition problem using CNN (Convolutional Neural Network) architectureĤ. MNIST_Classifier_MLP(Train_3D).vi - training the deep neural network for image classification task in handwritten digit recognition problem (based on MNIST database) on 3-dimensional dataset using MLP (Multilayer Perceptron) architectureģ. MNIST_Classifier_MLP(Train_1D).vi - training the deep neural network for image classification task in handwritten digit recognition problem (based on MNIST database) on 1 dimensional dataset using MLP (Multilayer Perceptron) architectureĢ. Stochastic Gradient Descend (SGD) based Backpropagation algorithm with Momentum and Weight decayĪdam - Stochastic gradient descent method which is based on adaptive estimation of first-order and second-order moments.Įxamples are available to demonstrate the applications of the toolkit in:ġ. Pooling (MaxPool, AvgPool, GlobalMax, GlobalAvg) ![]() Start with ready-to-run real-world examplesĪccelerate inference on FPGAs (with help of DeepLTK FPGA Add-on)Īugmentations: Noise, Flip(Vertical, Horizontal), Brightness, Contrast, Hue, Saturation, Shear, Scale(Zoom), Blur, Move.Īctivations: Linear(None), Sigmoid, tanh(Hyperbolic Tangent), ReLU(Rectified Linear Unit), LReLU(Leaky ReLU) Speed up pre-trained networks by employing network graph optimization utilitiesĪnalyze and evaluate network's performance Visualize network topology and common metrics (memory footprint, computational complexity)ĭeploy pre-trained networks on NI's LabVIEW Real-Time target for inference ![]() Save trained networks and load for deployment The toolkit is completely developed in LabVIEW and does not have any outer dependencies, which simplifies the installation, development, deployment and distribution of toolkit based applications and systems (particularly, can be easily deployed on NI's Real Time targets).Ĭreate, configure, train, and deploy deep neural networks (DNNs) in LabVIEWĪccelerate training and deployment of DNNs on GPUs DeepLTK is a Deep Learning Toolkit for LabVIEW providing high-level API to build, configure, visualize, train, analyze and deploy Deep Neural Networks within LabVIEW. ![]()
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