Neural Network with TensorFlow
A CONVOLUTIONAL NEURAL NETWORK (CNN) APPROACH TO DETECT FACE USING TENSORFLOW AND KERAS
... Using TensorFlow, which is an open-source artificial intelligence library developed by Google, we have studied and compared the effects of multiple activation functions on classification ...open-source ...
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Scaling a convolutional neural network for classification of adjective noun pairs with TensorFlow on GPU clusters
... Abstract—Deep neural networks have gained popularity in recent years, obtaining outstanding results in a wide range of applications such as computer vision in both academia and multiple industry ...deep ...
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Recognition of Handwritten Digit using Convolutional Neural Network in Python with Tensorflow and Comparison of Performance for Various Hidden Layers
... the network. It compares the output of the network with the desired ...Convolutional Neural Network algorithm on Modified National Institute of Standards and Technology (MNIST) dataset using ...
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TensorFlow and Keras based Convolutional Neural Network in CAT Image Recognition
... convolutional neural network model, 4 layers of convolution layers and two layers of common dense layers are ...the neural network in the human brain, and through a certain amount of learning, ...
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Implementation of Recurrent Neural Network with Sequence to Sequence Model to Translate Language Based on TensorFlow
... recurrent neural network based LM, a type of deep neural network for dealing with sequential data, have been proposed and achieved remarkable ...deep neural network with a ...
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Application of neural networks to the collision avoidance problem in 2D based on the TensorFlow library
... 1.2 Neural Networks for UAVs 5 Neural Networks for UAVs There are many researches about the usefulness of a neural network (NN) controlling an ...for Neural Network and a ...
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Getting Started - TensorFlow
... Examples TensorFlow Mechanics 101 Code: tensorflow/g3doc/tutorials/mnist/ The goal of this tutorial is to show how to use TensorFlow to train and evaluate a simple feed-forward neural ...
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TensorFlow for Machine Intelligence
... These kernels match patterns in images at a rudimentary level. A convolutional neural network matches edges and more by using a complex kernel it learned during training. The starting values for the kernel ...
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Tensorflow Machine Learning Cookbook
... The concept of a neural network has been around for decades. However, it only recently gained traction computationally because we now have the computational power to train large networks because of advances ...
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Tensorflow Cnn Example Code
... the network will learn only the parts of the image that truly represent the object in ...cnn neural network on them also predictably meant my ...whole network still expresses a single ...
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Tensorflow Dataset Map Example
... current tensorflow-datasets ...Using TensorFlow to time a Neural Network with ...your TensorFlow Dataset in batches map this allows you to transform the data using lambda ...with ...
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Predicting the number of likes on Instagram with TensorFlow
... Also, three is better than one; the idea of combining variable, image and text models has been a good choice. Our accuracy has definitely increased. The quality of a deep learning model is constrained by the quality of ...
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Facebook text posts classification with TensorFlow
... h W c W . (2) Figure 3 – Co-ocurence matrix Figure 4 – Skip-gram predicts surrounding words given the word Our predictive model learns the vec- tors by minimizing the loss function. In Word2vec, this happens ...
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Exploring Automatic Speech Recognition with TensorFlow
... The implementation of LAS network was not provided by the authors, and it was challenging to find one, although we finally succeed. Nabu [26] is an Automatic Speech Recognizer frame- work for end-to-end networks ...
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Object tracking in video with TensorFlow
... the network is composed by two fundamental cells types: sim- ple ones, that respond maximally to specific edge-like patterns inside their receptive field, and the complex ones, having larger receptive fields and ...
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Image recognition with Deep Learning techniques and TensorFlow
... Deep neural networks have gained popularity in recent years, obtaining outstanding results in a wide range of application, but most notoriously in computer vision and natural language processing ...in ...
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Neural Network
... The rst data are the UNEMPLOY series from the foregoing section with the nal 5 data used as test data. The results with H = 10 are summarized in table 1. The Lyapunov exponents don't show a convergence to a constant ...
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Neural Network
... An all-optical recurrent neural network using volume holograms has been reported by Stoll and Lee (1988). It operates as an implementation of the Hopfield net, seeking a minimum on an optically generated ...
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Performance Comparison of Binarized Neural Network with Convolutional Neural Network
... Convolutional Neural Networks (CNN) is one of the most popular architectures used in deep ...Binarized Neural Network (BNN) is also a neural network which consists of binary weights and ...
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Video Analysis with Image Recognition in TensorFlow
... the spam problem is not as prevalent as a few years ago due to the deployment of systems that diminish it. Furthermore, users have an increased awareness of typical spam content (e.g., emails, etc.) and they can ...
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