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

By:

Verdhan, Vaibhav

Publication details: Apress Ireland 2021Description: xxi, 308pISBN:

9781484283394

Subject(s):

DDC classification:

006.3/VER

Summary: 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.

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Holdings
Item type	Current library	Call number	Status	Notes	Date due	Barcode
Books	Symbiosis Institute of Computer Studies and Research Data Mining	006.3/VER (Browse shelf(Opens below))	Available	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.		SICSR-B-19680

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Previous	006.3/KUL/SHI Natural Language Processing Recipes: Unlocking Text Data with Machine Learning and Deep Learning using Python	006.3/MIC Applied Deep Learning with TensorFlow 2: Learn to Implement Advanced Deep Learning Techniques with Python	006.3/SAN Deep Reinforcement Learning with Python	006.3/VER Computer Vision Using Deep Learning: Neural Network Architectures with Python and Keras	006.312/BAR LEARNING TO LOVE DATA SCIENCE	006.312/ROI DATA MINING: A TUTORIAL-BASED PRIMER	006.35/KUL/SHI Natural Language Processing Projects: Build Next-Generation NLP Applications Using AI Techniques	Next

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.

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