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Advanced Deep Learning with TensorFlow 2 and Keras - Second Edition

You're reading from Advanced Deep Learning with TensorFlow 2 and Keras - Second Edition

Product type Book

Published in Feb 2020

Publisher Packt

ISBN-13 9781838821654

Pages 512 pages

Edition 2nd Edition

Languages

Concepts

Programming Language

Author (1):

Rowel Atienza

Table of Contents (16) Chapters

Preface

1. Introducing Advanced Deep Learning with Keras

2. Deep Neural Networks

3. Autoencoders

4. Generative Adversarial Networks (GANs)

5. Improved GANs

6. Disentangled Representation GANs

7. Cross-Domain GANs

8. Variational Autoencoders (VAEs)

9. Deep Reinforcement Learning

10. Policy Gradient Methods

11. Object Detection

12. Semantic Segmentation

13. Unsupervised Learning Using Mutual Information

14. Other Books You May Enjoy

15. Index

7. SSD objects in Keras

Listing 11.7.1, displayed shortly, shows the SSD class. Two main routines are illustrated:

Creation of the SSD model using build_model()

Instantiating a data generator through build_generator()

build_model first creates a data dictionary from the train labels. The dictionary stores image filenames and ground truth bounding box coordinates and class for every object in each image. Afterward, the backbone and SSD network models are constructed. The most important product of model creation is self.ssd – the network model of SSD.

The labels are stored in a csv file. For the sample training images that is used in this book, the labels are saved in dataset/drinks/labels_train.csv with the format:

frame,xmin,xmax,ymin,ymax,class_id
0001000.jpg,310,445,104,443,1
0000999.jpg,194,354,96,478,1
0000998.jpg,105,383,134,244,1
0000997.jpg,157,493,89,194,1
0000996.jpg,51,435,207,347,1
0000995.jpg,183,536,156,283,1
0000994...

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Authors (1)

Rowel Atienza

Rowel Atienza is an Associate Professor at the Electrical and Electronics Engineering Institute of the University of the Philippines, Diliman. He holds the Dado and Maria Banatao Institute Professorial Chair in Artificial Intelligence. Rowel has been fascinated with intelligent robots since he graduated from the University of the Philippines. He received his MEng from the National University of Singapore for his work on an AI-enhanced four-legged robot. He finished his Ph.D. at The Australian National University for his contribution on the field of active gaze tracking for human-robot interaction. Rowel's current research work focuses on AI and computer vision. He dreams on building useful machines that can perceive, understand, and reason. To help make his dreams become real, Rowel has been supported by grants from the Department of Science and Technology (DOST), Samsung Research Philippines, and Commission on Higher Education-Philippine California Advanced Research Institutes (CHED-PCARI).

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