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Machine Learning with Core ML

You're reading from   Machine Learning with Core ML An iOS developer's guide to implementing machine learning in mobile apps

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Product type Paperback
Published in Jun 2018
Publisher Packt
ISBN-13 9781788838290
Length 378 pages
Edition 1st Edition
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Author (1):
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Joshua Newnham Joshua Newnham
Author Profile Icon Joshua Newnham
Joshua Newnham
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Table of Contents (12) Chapters Close

Preface 1. Introduction to Machine Learning FREE CHAPTER 2. Introduction to Apple Core ML 3. Recognizing Objects in the World 4. Emotion Detection with CNNs 5. Locating Objects in the World 6. Creating Art with Style Transfer 7. Assisted Drawing with CNNs 8. Assisted Drawing with RNNs 9. Object Segmentation Using CNNs 10. An Introduction to Create ML 11. Other Books You May Enjoy

Object localization and object detection 

As mentioned in the introduction of this chapter, we have already been introduced to the concepts behind object recognition using CNNs. For this case, we used a trained model to perform classification; it achieved this by learning a set of feature maps using convolutional layers that are fed into fully connected (or dense) layers and, finally, their output, through an activation layer which gave us the probability for each of the classes. The class was inferred by selecting the one with the largest probability. 

Let's differentiate between object recognition, object localization, and object detection. Object recognition is the task of classifying the most dominant object in a image while object localization performs classification and predicts an object's bounding box. Object detection further extends this and allows...
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