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Hands-On Neural Network Programming with C#

You're reading from   Hands-On Neural Network Programming with C# Add powerful neural network capabilities to your C# enterprise applications

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Product type Paperback
Published in Sep 2018
Publisher Packt
ISBN-13 9781789612011
Length 328 pages
Edition 1st Edition
Languages
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Author (1):
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Matt Cole Matt Cole
Author Profile Icon Matt Cole
Matt Cole
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Table of Contents (16) Chapters Close

Preface 1. A Quick Refresher FREE CHAPTER 2. Building Our First Neural Network Together 3. Decision Trees and Random Forests 4. Face and Motion Detection 5. Training CNNs Using ConvNetSharp 6. Training Autoencoders Using RNNSharp 7. Replacing Back Propagation with PSO 8. Function Optimizations: How and Why 9. Finding Optimal Parameters 10. Object Detection with TensorFlowSharp 11. Time Series Prediction and LSTM Using CNTK 12. GRUs Compared to LSTMs, RNNs, and Feedforward networks 13. Activation Function Timings
14. Function Optimization Reference 15. Other Books You May Enjoy

Object Detection with TensorFlowSharp

In this chapter, we are going to introduce you to an open source package called TensorFlowSharp. More specifically, we will be using the TensorFlow[1] Object Detection API, which is an open source framework built on top of TensorFlow, which makes it easy to construct, train, and deploy various forms of object detection models.

For those not familiar with TensorFlow, the following is an excerpt from the TensorFlow website[2]:

"TensorFlow is an open source software library for high performance numerical computation. Its flexible architecture allows easy deployment of computation across a variety of platforms (such as CPUs, GPUs, and TPUs), and from desktops to clusters of servers to mobile and edge devices. Originally developed by researchers and engineers from the Google Brain team within Google's AI organization, it comes with strong...
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