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Create image processing, object detection and face recognition apps by leveraging the power of machine learning and deep learning with OpenCV 4 and Qt 5Key FeaturesGain practical …
Updated for OpenCV 4 and Python 3, this book covers the latest on depth cameras, 3D tracking, augmented reality, and deep neural networks, helping you solve real-world computer …
Learn how to model and train advanced neural networks to implement a variety of Computer Vision tasksKey Features Train different kinds of deep learning model from scratch to solve …
Blend the power of Qt with OpenCV to build cross-platform computer vision applications Key Features ? Start creating robust applications with the power of OpenCV and Qt combined? …
Discover how to integrate KNIME Analytics Platform with deep learning libraries to implement artificial intelligence solutionsKey FeaturesBecome well-versed with KNIME Analytics …
Unleash the full potential of transformers with this comprehensive guide covering architecture, capabilities, risks, and practical implementations on OpenAI, Google Vertex AI, and …
Get to grips with traditional computer vision algorithms and deep learning approaches, and build real-world applications with OpenCV and other machine learning frameworksKey …
Build smarter applications with AI capabilities using Microsoft Cognitive Services APIs without much hassleKey FeaturesExplore the Cognitive Services APIs for building machine …
Turn futuristic ideas about computer vision and machine learning into demonstrations that are both functional and entertainingKey FeaturesBuild OpenCV 4 apps with Python 2 and 3 on …
Fun and exciting projects to learn what artificial minds can createKey FeaturesCode examples are in TensorFlow 2, which make it easy for PyTorch users to follow alongLook inside …