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Applied Cloud Deep Semantic Recognition

application domains. This book provides a better understanding of the different directions in which research has been done on deep semantic analysis;

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Bridging the Semantic Gap in Image and Video Analysis

third is object recognition, and the fourth and last involve the semantic interpretation of the image. The semantic gap is a challenging area;

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Concepts and Real-Time Applications of Deep Learning

architecture with applications in natural language processing, semantic knowledge, forecasting and many more. The authors shed light on various;

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Performance Evaluation of Cloud Services

Performance Evaluation of Cloud Services evaluates various aspects of cloud services and its computing measures for various multi-tier;

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Deep Learning in Computer Vision

, face recognition, action and activity recognition, semantic segmentation for autonomous driving, aerial imagery registration, robot vision;

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Machine Learning for Speaker Recognition

This book will help readers understand fundamental and advanced statistical models and deep learning models for robust speaker recognition;

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TensorFlow 2 x in the Colaboratory Cloud

Use TensorFlow 2.x with Google's Colaboratory (Colab) product that offers a free cloud service for Python programmers. Colab is especially;

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Deep Learning Approaches to Cloud Security

DEEP LEARNING APPROACHES TO CLOUD SECURITY Covering one of the most important subjects to our society today, cloud security, this editorial;

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Handbook of Deep Learning Applications

object recognition, driverless cars, semantic image segmentation, deep visual residual abstraction, brain-computer interfaces, big data;

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Deep Learning in Computer Vision: Principles and Applications

, face recognition, action and activity recognition, semantic segmentation for autonomous driving, aerial imagery registration, robot vision;

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Intelligent Scene Modeling and Human-Computer Interaction

Recognition and Speech Synthesis will replace the traditional mouse and keyboard interfaces * Semantic modeling and rendering and shows how;

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Mission Oriented Sensor Networks and Systems Art and Science

object recognition, driverless cars, semantic image segmentation, deep visual residual abstraction, brain-computer interfaces, big data;

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Mastering Computer Vision with TensorFlow 2.x

recognition. You'll then discover how to develop powerful neural network models on your PC and on various cloud platforms. Finally, you'll learn to;

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Building Intelligent Cloud Applications Develop Scalable Models Using Serverless Architectures with Azure

Serverless computing is radically changing the way we build and deploy applications. With cloud providers running servers and managing;

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Geographical Information Systems

Web services, cloud computing, location based services, NoSQLdatabases, and Semantic Web offer new ways of accessing, analyzing, and;

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Semantic Priming

investigating other aspects of perception and cognition, such as word recognition, language comprehension, and knowledge representations. Semantic;

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Semantic Priming

investigating other aspects of perception and cognition, such as word recognition, language comprehension, and knowledge representations. Semantic;

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Practical AI on the Google Cloud Platform Utilizing Google's StateoftheArt AI Cloud Services

Working with AI is complicated and expensive for many developers. That's why cloud providers have stepped in to make it easier, offering;

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Computer Vision ECCV 2020

. The papers deal with topics such as computer vision; machine learning; deep neural networks; reinforcement learning; object recognition; image;

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Computer Vision - ACCV 2016. Part 5

Semantic Segmentation; Dictionary Learning, Retrieval, and Clustering; Deep Learning; People Tracking and Action Recognition; People and Actions;

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Computer Vision ECCV 2020

. The papers deal with topics such as computer vision; machine learning; deep neural networks; reinforcement learning; object recognition; image;

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Computer Vision ECCV 2020

. The papers deal with topics such as computer vision; machine learning; deep neural networks; reinforcement learning; object recognition; image;

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Computer Vision - ACCV 2016

Semantic Segmentation; Dictionary Learning, Retrieval, and Clustering; Deep Learning; People Tracking and Action Recognition; People and Actions;

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Computer Vision ECCV 2020

. The papers deal with topics such as computer vision; machine learning; deep neural networks; reinforcement learning; object recognition; image;

Vergelijkbare producten zoals Computer Vision ECCV 2020

Computer Vision ECCV 2020

. The papers deal with topics such as computer vision; machine learning; deep neural networks; reinforcement learning; object recognition; image;

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Computer Vision - ACCV 2016. Part 1

Semantic Segmentation; Dictionary Learning, Retrieval, and Clustering; Deep Learning; People Tracking and Action Recognition; People and Actions;

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Computer Vision - ACCV 2016

Semantic Segmentation; Dictionary Learning, Retrieval, and Clustering; Deep Learning; People Tracking and Action Recognition; People and Actions;

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