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Machine Learning Methods for Visual Object Detection

Sparsification) and learning methods (Latent and Non-Latent Support Vector Machines) for the problem of object detection. These methods are presented;

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Machine Learning and Visual Perception

, face recognition, deep learning, time series recognition, image classification, and object detection.;

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Visual Perception and Control of Underwater Robots

. Within the framework of visual perception for underwater operations, image restoration, binocular measurement, and object detection are addressed;

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Visual Perception and Control of Underwater Robots

. Within the framework of visual perception for underwater operations, image restoration, binocular measurement, and object detection are addressed;

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Applications of Advanced Machine Intelligence in Computer Vision and Object Recognition

disease detection, adaptive learning, and automated image segmentation, this book is ideally designed for engineers, physicians, researchers;

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Applications of Advanced Machine Intelligence in Computer Vision and Object Recognition

disease detection, adaptive learning, and automated image segmentation, this book is ideally designed for engineers, physicians, researchers;

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Visual Saliency

object detection. For low-level tasks, the authors focus on pixel-level image processing approaches based on efficient distance;

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Machine Learning for Vision-Based Motion Analysis: Theory and Techniques

application of statistical machine learning algorithms for object tracking, activity modeling, and recognition. Developed from expert contributions;

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Beginning Anomaly Detection Using Python-Based Deep Learning

statistical and traditional machine learning methods for anomaly detection using Scikit-Learn in Python, the book then provides an introduction to;

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Machine Learning Applications for Accounting Disclosure and Fraud Detection

is provided towards the prediction of the actual financial performance of the business activity. Machine Learning Applications for Accounting;

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Domain Adaptation for Visual Understanding

This unique volume reviews the latest advances in domain adaptation in the training of machine learning algorithms for visual understanding;

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Domain Adaptation for Visual Understanding

This unique volume reviews the latest advances in domain adaptation in the training of machine learning algorithms for visual understanding;

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Mastering Computer Vision with TensorFlow 2.x

, image classification, and object detection Develop deep learning models on cloud platforms and optimize them using TensorFlow Lite and the;

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Advances in Visual Computing

Learning II; Virtual Reality II; Object RecognitionDetection/Categorization; and Poster.;

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Challenges and Applications for Implementing Machine Learning in Computer Vision

collection of innovative research that combines theory and practice on adopting the latest deep learning advancements for machines capable of visual;

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Challenges and Applications for Implementing Machine Learning in Computer Vision

collection of innovative research that combines theory and practice on adopting the latest deep learning advancements for machines capable of visual;

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Hybrid Machine Intelligence for Medical Image Analysis

the latest trends in machine learning technologies and computational intelligence for intelligent medical image analysis. The topics covered;

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Python Advanced Guide to Artificial Intelligence: Advanced Guide to Artificial Intelligence: Expert machine learning systems and intelligent agents us

supervised, unsupervised, and semi-supervised ML algorithms and their implementation Build deep learning models for object detection, image;

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Machine Learning in Radiation Oncology

individual sections are then devoted to the use of machine learning in quality assurance; computer-aided detection, including treatment planning and;

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Pattern Recognition and Computer Vision

reviewed and selected from 513 submissions. The papers have been organized in the following topical sections: Object Detection, Tracking and;

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Network Anomaly Detection

security, credit card and insurance fraud detection, and military surveillance for enemy activities. Network Anomaly Detection: A Machine Learning;

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Data Mining and Machine Learning in Cybersecurity

techniques for detecting new attacks Contains in-depth discussions of machine learning solutions to detection problems Categorizes methods for;

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Hands-On Image Processing with Python

processing Use deep learning models for image classification, segmentation, object detection and style transfer Who this book is forThis book is for;

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Python Image Processing Cookbook

-image and Keras Learn popular concepts such as machine learning, deep learning, and neural networks for image processing Explore common and not;

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Machine Learning for Subsurface Characterization

Machine Learning for Subsurface Characterization develops and applies neural networks, random forests, deep learning, unsupervised learning;

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Density Ratio Estimation in Machine Learning

machine learning community. Various machine learning problems such as non-stationarity adaptation, outlier detection, dimensionality reduction;

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Density Ratio Estimation in Machine Learning

machine learning community. Various machine learning problems such as non-stationarity adaptation, outlier detection, dimensionality reduction;

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