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Deep Learning for Computer Vision: Expert techniques to train advanced neural networks using TensorFlow and Keras
Deep Learning for Computer Vision: Expert techniques to train advanced neural networks using TensorFlow and Keras

Learn how to model and train advanced neural networks to implement a variety of Computer Vision tasks

Key Features

  • Train different kinds of deep learning model from scratch to solve specific problems in Computer Vision
  • Combine the power of Python, Keras, and TensorFlow to...
Practical Convolutional Neural Networks: Implement advanced deep learning models using Python
Practical Convolutional Neural Networks: Implement advanced deep learning models using Python

One stop guide to implementing award-winning, and cutting-edge CNN architectures

Key Features

  • Fast-paced guide with use cases and real-world examples to get well versed with CNN techniques
  • Implement CNN models on image classification, transfer learning, Object Detection,...
Mastering OpenCV 4 with Python: A practical guide covering topics from image processing, augmented reality to deep learning with OpenCV 4 and Python 3.7
Mastering OpenCV 4 with Python: A practical guide covering topics from image processing, augmented reality to deep learning with OpenCV 4 and Python 3.7

Create advanced applications with Python and OpenCV, exploring the potential of facial recognition, machine learning, deep learning, web computing and augmented reality.

Key Features

  • Develop your computer vision skills by mastering algorithms in Open Source Computer Vision 4 (OpenCV 4)and...
Unity 2018 Augmented Reality Projects: Build four immersive and fun AR applications using ARkit, ARCore, and Vuforia
Unity 2018 Augmented Reality Projects: Build four immersive and fun AR applications using ARkit, ARCore, and Vuforia

Create engaging Augmented Reality (AR) applications with Unity 3D that can be experienced with devices such as HoloLens and Daydream

Key Features

  • Learn the principles of AR application development
  • Work with the most popular sensors used in AR games and applications across...
Apache Spark Deep Learning Cookbook: Over 80 recipes that streamline deep learning in a distributed environment with Apache Spark
Apache Spark Deep Learning Cookbook: Over 80 recipes that streamline deep learning in a distributed environment with Apache Spark

A solution-based guide to put your deep learning models into production with the power of Apache Spark

Key Features

  • Discover practical recipes for distributed deep learning with Apache Spark
  • Learn to use libraries such as Keras and TensorFlow
  • Solve...
Scientific Computing with Python 3
Scientific Computing with Python 3

Key Features

  • Your ultimate resource for getting up and running with Python numerical computations
  • Explore numerical computing and mathematical libraries using Python 3.x code with SciPy and NumPy modules
  • A hands-on guide to implementing mathematics with Python, with complete...
Handbook of Multisensor Data Fusion
Handbook of Multisensor Data Fusion

Multisensor data fusion is an emerging technology with important applications in both the military and civilian sectors, such as target recognition, robotics, medical diagnostics, and "smart" buildings. It draws on techniques from wide-ranging disciplines, including artificial intelligence, pattern recognition, and statistical...

Handbook of Geometric Computing: Applications in Pattern Recognition, Computer Vision, Neuralcomputing, and Robotics
Handbook of Geometric Computing: Applications in Pattern Recognition, Computer Vision, Neuralcomputing, and Robotics
Many computer scientists, engineers, applied mathematicians, and physicists use geometry theory and geometric computing methods in the design of perception-action systems, intelligent autonomous systems, and man-machine interfaces. This handbook brings together the most recent advances in the application of geometric computing for building such...
Data Model Patterns: A Metadata Map (The Morgan Kaufmann Series in Data Management Systems)
Data Model Patterns: A Metadata Map (The Morgan Kaufmann Series in Data Management Systems)
A very ambitious undertaking, masterfully described. To the best of my knowledge, this is the first published version of the detailed models implied by the Zachman Framework. David Hay builds the models one step at a time, describing in each increment why the new entities were added, and how they related to the rest of the model. At least as...
Automatic Algorithm Recognition and Replacement: A New Approach to Program Optimization
Automatic Algorithm Recognition and Replacement: A New Approach to Program Optimization
Optimizing compilers have a fundamental problem. No matter how powerful their optimizations
are, they are no substitute for good application algorithms. Consider the case of
sorting. For sufficiently large data sets, a merge sort algorithm compiled with a less powerful
optimizer will always out-perform a selection sort algorithm
...
The Fifth Postulate: How Unraveling A Two Thousand Year Old Mystery Unraveled the Universe
The Fifth Postulate: How Unraveling A Two Thousand Year Old Mystery Unraveled the Universe
What do Einstein's theory of relativity, string theory, and lots of other mind-bending—and space-bending—revelations of modern physics have in common? None of them could have been discovered until scientists and mathematicians recognized an uncomfortable truth—that there was a reason the world's greatest mathematical minds had...
Introduction to Artificial Neural Systems
Introduction to Artificial Neural Systems
The recent resurgence of interest in neural networks has its roots in the recognition that the brain performs computations in a different manner than do conventional digital computers. Computers are extremely fast and precise at executing sequences of instructions that have been formulated for them. A human information processing system is composed...
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