Computer Vision Using Deep Learning: Neural Network Architectures with Python, Keras, and Tensorflow

Organizations spend huge resources in developing software that can perform the way a human does. Image classification, object detection and tracking, pose estimation, facial recognition, and sentiment estimation all play a major role in solving computer vision problems.

This book will bring into focus these and other deep learning architectures and techniques to help you create solutions using Keras and the TensorFlow library. You’ll also review mutliple neural network architectures, including LeNet, AlexNet, VGG, Inception, R-CNN, Fast R-CNN, Faster R-CNN, Mask R-CNN, YOLO, and SqueezeNet and see how they work alongside Python code via best practices, tips, tricks, shortcuts, and pitfalls. All code snippets will be broken down and discussed thoroughly so you can implement the same principles in your respective environments.

Computer Vision Using Deep Learning offers a comprehensive yet succinct guide that stitches DL and CV together to automate operations, reduce human intervention, increase capability, and cut the costs.

What You’ll Learn

• Examine deep learning code and concepts to apply guiding principals to your own projects
• Classify and evaluate various architectures to better understand your options in various use cases
• Go behind the scenes of basic deep learning functions to find out how they work

Who This Book Is For

Professional practitioners working in the fields of software engineering and data science. A working knowledge of Python is strongly recommended. Students and innovators working on advanced degrees in areas related to computer vision and Deep Learning.

Vaibhav Verdhan is the Principal Data Scientist at Johnson & Johnson. He has more than a decade of professional experience in the fields of data science, machine learning, and artificial intelligence with in-depth experience in leading multiple engagements in those fields as well as analytics consulting. Viabhav is an industry leader with global client exposure across UK, Ireland, UAE, KSA, India, and South Africa in retail, telecom, manufacturing, insurance, and energy utilities domains. He is a hands-on technical expert with acumen to assimilate and analyze data and draw meaningful insights thereby leading to strategic planning and decision making.