Discover the essential building blocks of a common and powerful form of deep belief net: the autoencoder. You’ll take this topic beyond current usage by extending it to the complex domain for signal and image processing applications. Deep Belief Nets in C++ and CUDA C: Volume 2 also covers several...
Create image processing, object detection and face recognition apps by leveraging the power of machine learning and deep learning with OpenCV 4 and Qt 5
Key Features
Gain practical insights into code for all projects covered in this book
Build GPU-accelerated high performing applications with Python 2.7, CUDA 9, and open source libraries such as PyCUDA and scikit-cuda. We recommend the use of Python 2.7 as this version has stable support across all libraries used in this book.
Discover the essential building blocks of a common and powerful form of deep belief network: convolutional nets. This book shows you how the structure of these elegant models is much closer to that of human brains than traditional neural networks; they have a ‘thought process’ that is capable of learning abstract...
