Video Analytics Using Deep Learning

- Building Applications with TensorFlow, Keras, and YOLO

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Video Analytics Using Deep Learning
  • Leveringstid Mangler, normalt 2-5 uger
Format:
Bog, paperback
Udgivelsesdato:
13-01-2020
Sprog:
Engelsk
Udgave:
1st ed..
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Build analytics for video using TensorFlow, Keras, and YOLO. This book guides you through the field of deep learning starting with neural networks, taking a deep dive into convolutional neural networks, recurrent neural networks, and long short-term memory (LSTM) networks. Video Analytics Using Deep Learning closes with practical examples of building image filters and video masking using generative models. The examples within the book cover topics from domains such as traffic recognition for self-driving cars; face recognition and emotion analysis for retail analytics; object and tamper detection for safety and security; and image filters and video masking for social networks and web applications. To enable you to make a smooth transition into deep learning, the book covers mathematical pre-requisites and includes an introduction to deep learning. You'll also cover topics such as storage of large video content for processing on the cloud and working with the connectors involved. All the code and samples in the book are provided as iPython. What You Will LearnMaster TensorFlow, Keras, and YOLOWork with face recognition, age detection, and gender identificationApply CNN, RNN and generative models in deep learningUse emotion analysis and gesture detectionCarry out traffic recognition in real-timeWho This Book Is ForData scientists and machine learning developers looking to build applications based on video in finance, healthcare, automotive, transport, safety/security, and home automation.

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Udgivelsesdato:
13-01-2020
ISBN13:
9781484237922
Bredde:
178 mm
Højde:
254 mm
Forlag:
Apress
Format:
Paperback
Forfattere
Bibliotekernes beskrivelse This book guides you through the field of deep learning starting with neural networks, taking a deep dive into convolutional neural networks, recurrent neural networks, and long short-term memory (LSTM) networks. 1 Paperback / softback XV, 265 p.

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