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Practical Convolutional Neural Networks

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

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Product type Paperback
Published in Feb 2018
Publisher Packt
ISBN-13 9781788392303
Length 218 pages
Edition 1st Edition
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Authors (3):
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Mohit Sewak Mohit Sewak
Author Profile Icon Mohit Sewak
Mohit Sewak
Md. Rezaul Karim Md. Rezaul Karim
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Md. Rezaul Karim
Pradeep Pujari Pradeep Pujari
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Pradeep Pujari
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Table of Contents (11) Chapters Close

Preface 1. Deep Neural Networks – Overview FREE CHAPTER 2. Introduction to Convolutional Neural Networks 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

References


  1. Kelvin Xu, Jimmy Ba, Ryan Kiros, Kyunghyun Cho, Aaron C. Courville, Ruslan Salakhutdinov, Richard S. Zemel, Yoshua Bengio, Show, Attend and Tell: Neural Image Caption Generation with Visual Attention, CoRR, arXiv:1502.03044, 2015.
  2. Karl Moritz Hermann, Tom's Kocisk, Edward Grefenstette, Lasse Espeholt, Will Kay, Mustafa Suleyman, Phil Blunsom, Teaching Machines to Read and Comprehend, CoRR, arXiv:1506.03340, 2015.
  3. Volodymyr Mnih, Nicolas Heess, Alex Graves, Koray Kavukcuoglu, Recurrent Models of Visual Attention, CoRR, arXiv:1406.6247, 2014.
  4. Long Chen, Hanwang Zhang, Jun Xiao, Liqiang Nie, Jian Shao, Tat-Seng Chua, SCA-CNN: Spatial and Channel-wise Attention in Convolutional Networks for Image Captioning, CoRR, arXiv:1611.05594, 2016.
  5. Kan Chen, Jiang Wang, Liang-Chieh Chen, Haoyuan Gao, Wei Xu, Ram Nevatia, ABC-CNN: An Attention Based Convolutional Neural Network for Visual Question Answering, CoRR, arXiv:1511.05960, 2015.
  6. Wenpeng Yin, Sebastian Ebert, Hinrich Schutze, Attention-Based...
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