Book Image

Practical Convolutional Neural Networks

By : Mohit Sewak, Md. Rezaul Karim, Pradeep Pujari
Book Image

Practical Convolutional Neural Networks

By: Mohit Sewak, Md. Rezaul Karim, Pradeep Pujari

Overview of this book

Convolutional Neural Network (CNN) is revolutionizing several application domains such as visual recognition systems, self-driving cars, medical discoveries, innovative eCommerce and more.You will learn to create innovative solutions around image and video analytics to solve complex machine learning and computer vision related problems and implement real-life CNN models. This book starts with an overview of deep neural networkswith the example of image classification and walks you through building your first CNN for human face detector. We will learn to use concepts like transfer learning with CNN, and Auto-Encoders to build very powerful models, even when not much of supervised training data of labeled images is available. Later we build upon the learning achieved to build advanced vision related algorithms for object detection, instance segmentation, generative adversarial networks, image captioning, attention mechanisms for vision, and recurrent models for vision. By the end of this book, you should be ready to implement advanced, effective and efficient CNN models at your professional project or personal initiatives by working on complex image and video datasets.
Table of Contents (11 chapters)


  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...