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Machine Learning Methods for Behaviour Analysis and Anomaly Detection in Video

This thesis proposes machine learning methods for understanding scenes via behaviour analysis and online anomaly detection in video. The;

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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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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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Traffic Anomaly Detection

"typical day analysis". A new information-theory based technique for traffic anomaly detection (typical day analysis)

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Kernel Methods for Remote Sensing Data Analysis

, multi-temporal image classification, target detection with kernels, and Support Vector Data Description (SVDD) algorithms for anomaly detection;

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Machine Learning with the Elastic Stack

create anomaly detection jobs and view results from Kibana directly. What you will learn Install the Elastic Stack to use machine learning;

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Anomaly Detection

of data is called anomaly detection. With progress in the technologies and the widespread use of data for the purpose for business the increase;

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Machine Learning in Medicine

networks, discrete wavelet analysis, association rule learning, anomaly detection, and correspondence analysis. This third volume addresses more;

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Pattern Recognition

; action and video and motion; object detection and anomaly detection; segmentation, grouping and shape; face and body and biometrics; adversarial;

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Pattern Recognition

; action and video and motion; object detection and anomaly detection; segmentation, grouping and shape; face and body and biometrics; adversarial;

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Anomaly-Detection and Health-Analysis Techniques for Core Router Systems

This book tackles important problems of anomaly detection and health status analysis in complex core router systems, integral to today's;

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Anomaly-Detection and Health-Analysis Techniques for Core Router Systems

This book tackles important problems of anomaly detection and health status analysis in complex core router systems, integral to today's;

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

to the first and second International Workshop on Machine Learning for Vision-Based Motion Analysis, this important text/reference highlights;

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Practical Machine Learning - A New Look at Anomaly Detection

, medicine, and marketing, anomaly detection has many useful applications in this age of big data. And the search for anomalies will intensify once;

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Machine Learning and Knowledge Discovery in Databases

track. The contributions were organized in topical sections named as follows: Part I: adversarial learning; anomaly and outlier;

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Cyber Security Cryptography and Machine Learning

anonymity; post-quantum cryptography and security; machine learning and big data; anomaly detection and malware identification; business;

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Machine Learning and Knowledge Discovery in Databases

. The contributions were organized in topical sections named as follows: Part I: adversarial learning; anomaly and outlier detection;

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Machine Learning and Knowledge Discovery in Databases

. The contributions were organized in topical sections named as follows: Part I: adversarial learning; anomaly and outlier detection;

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Machine Learning and Knowledge Discovery for Engineering Systems Health Management

systems health management. The first part of the text describes data-driven methods for anomaly detection, diagnosis, and prognosis of massive;

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Applied Unsupervised Learning with R

, principal component analysis, and anomaly detection. You'll be introduced to these methods using code written in R, with further instructions on how;

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Behavior Analysis with Machine Learning Using R

Behavior Analysis with Machine Learning Using R introduces machine learning and deep learning concepts and algorithms applied to a diverse;

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Multiple-Aspect Analysis of Semantic Trajectories

data representation models, data management systems, machine learning approaches for anomaly detection, and common pathways identification.;

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Applied Cloud Deep Semantic Recognition

frameworks for deep semantic analysis and advanced anomaly detection using cognitive and artificial intelligence (AI) models.;

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Anomaly Detection and Complex Event Processing Over IoT Data Streams

advanced processing techniques for IoT data streams and the anomaly detection algorithms over them. The book brings new advances and generalized;

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Conformal Prediction for Reliable Machine Learning

financial risk prediction. Conformal Predictions for Reliable Machine Learning: Theory, Adaptations and Applications captures the basic theory;

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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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Mastering Machine Learning with R -

insights into the application of machine learning tools in the industry * Manipulate data in R efficiently to prepare it for analysis * Master;

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