Search icon CANCEL
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Practical Convolutional Neural Networks

You're reading from   Practical Convolutional Neural Networks Implement advanced deep learning models using Python

Arrow left icon
Product type Paperback
Published in Feb 2018
Publisher Packt
ISBN-13 9781788392303
Length 218 pages
Edition 1st Edition
Languages
Tools
Arrow right icon
Authors (3):
Arrow left icon
Mohit Sewak Mohit Sewak
Author Profile Icon Mohit Sewak
Mohit Sewak
Md. Rezaul Karim Md. Rezaul Karim
Author Profile Icon Md. Rezaul Karim
Md. Rezaul Karim
Pradeep Pujari Pradeep Pujari
Author Profile Icon Pradeep Pujari
Pradeep Pujari
Arrow right icon
View More author details
Toc

Table of Contents (11) Chapters Close

Preface 1. Deep Neural Networks – Overview 2. Introduction to Convolutional Neural Networks FREE CHAPTER 3. Build Your First CNN and Performance Optimization 4. Popular CNN Model Architectures 5. Transfer Learning 6. Autoencoders for CNN 7. Object Detection and Instance Segmentation with CNN 8. GAN: Generating New Images with CNN 9. Attention Mechanism for CNN and Visual Models 10. Other Books You May Enjoy

Convolutional neural networks

CNNs, or ConvNets, are quite similar to regular neural networks. They are still made up of neurons with weights that can be learned from data. Each neuron receives some inputs and performs a dot product. They still have a loss function on the last fully connected layer. They can still use a nonlinearity function. All of the tips and techniques that we learned from the last chapter are still valid for CNN. As we saw in the previous chapter, a regular neural network receives input data as a single vector and passes through a series of hidden layers. Every hidden layer consists of a set of neurons, wherein every neuron is fully connected to all the other neurons in the previous layer. Within a single layer, each neuron is completely independent and they do not share any connections. The last fully connected layer, also called the output layer...

You have been reading a chapter from
Practical Convolutional Neural Networks
Published in: Feb 2018
Publisher: Packt
ISBN-13: 9781788392303
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime