Advanced Applied Deep Learning: Convolutional Neural Networks and Object Detection
Authors: Umberto Michelucci
ISBN-10: 1484249755
ISBN-13: 9781484249758
Edition 版本: 1st ed.
Released: 2019-09-29
Print Length 页数: 304 pages
Book Description
Develop and optimize deep learning models with advanced architectures. This book teaches you the intricate details and subtleties of the algorithms that are at the core of convolutional neural networks. In Advanced Applied Deep Learning,you will study advanced topics on CNN and object detection using Keras and TensorFlow.
Along the way,you will look at the fundamental operations in CNN,such as convolution and pooling,and then look at more advanced architectures such as inception networks,resnets,and many more. While the book discusses theoretical topics,you will discover how to work efficiently with Keras with many tricks and tips,including how to customize logging in Keras with custom callback classes,what is eager execution,and how to use it in your models.
Finally,you will study how object detection works,and build a complete implementation of the YOLO (you only look once) algorithm in Keras and TensorFlow. By the end of the book you will have implemented various models in Keras and learned many advanced tricks that will bring your skills to the next level.
What You Will Learn
See how convolutional neural networks and object detection work
Save weights and models on disk
Pause training and restart it at a later stage
Use hardware acceleration (GPUs) in your code
Work with the Dataset TensorFlow abstraction and use pre-trained models and transfer learning
Remove and add layers to pre-trained networks to adapt them to your specific project
Apply pre-trained models such as Alexnet and VGG16 to new datasets
1.Introduction and Development Environment Setup
2.TensorFlow: Advanced Topics
3.Fundamentals of Convolutional Neural Networks
4.Advanced CNNs and Transfer Learning
5.Cost Functions and Style Transfer
6.Object Classifncation: An Introduction
7.Object Localization: An Iimplementation in Python
8.Histology Tissue Classification
