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Neural Network Projects with Python

You're reading from  Neural Network Projects with Python

Product type Book
Published in Feb 2019
Publisher Packt
ISBN-13 9781789138900
Pages 308 pages
Edition 1st Edition
Languages
Author (1):
James Loy James Loy
Profile icon James Loy

Table of Contents (10) Chapters

Preface 1. Machine Learning and Neural Networks 101 2. Predicting Diabetes with Multilayer Perceptrons 3. Predicting Taxi Fares with Deep Feedforward Networks 4. Cats Versus Dogs - Image Classification Using CNNs 5. Removing Noise from Images Using Autoencoders 6. Sentiment Analysis of Movie Reviews Using LSTM 7. Implementing a Facial Recognition System with Neural Networks 8. What's Next? 9. Other Books You May Enjoy

Types of object recognition tasks

It is important to understand the different kinds of object recognition tasks, as the required neural network architecture greatly depends on the task. Object recognition tasks can be broadly classified into three different types:

  • Image classification
  • Object detection
  • Instance segmentation

The following diagram depicts the difference between each task:

In Image Classification, the input to the problem is an image and the required output is simply a prediction of the class that the image belongs to. This is analogous to our first project, where we constructed a classifier to predict whether a patient is at risk of diabetes. In image classification, the problem is applied on pixels as our input data (specifically, the intensity value of each pixel), instead of tabular data represented by pandas DataFrames. In this project, we will focus on image...

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