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Titlebook: Anomaly Detection in Video Surveillance; Xiaochun Wang Book 2024 The Editor(s) (if applicable) and The Author(s), under exclusive license

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發(fā)表于 2025-3-25 07:17:18 | 只看該作者
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發(fā)表于 2025-3-25 10:23:54 | 只看該作者
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發(fā)表于 2025-3-25 12:13:39 | 只看該作者
Introduction,tant component of the global information infrastructure. Surveillance video has become the largest part of global big data, containing rich information and having great practical significance for intelligent analysis. Abnormal behavior detection techniques in video scenes are the core technology of
24#
發(fā)表于 2025-3-25 19:44:12 | 只看該作者
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發(fā)表于 2025-3-26 02:53:32 | 只看該作者
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發(fā)表于 2025-3-26 05:11:18 | 只看該作者
Gaussian Mixture Model-Based Video Anomaly Detection,extracted from a normal video are decomposed into a set of Gaussian components that, after learning, can then be used to detect the pixels that deviate from the established background model and therefore regarded to belong to the foreground objects.
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發(fā)表于 2025-3-26 08:47:21 | 只看該作者
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發(fā)表于 2025-3-26 16:35:35 | 只看該作者
Support Vector Machine-Based Video Anomaly Detection Approaches,e a general description of this supervised learning algorithm which consists of a training stage and a testing stage. More specifically, in the training stage, a set of labeled source outputs, that is, the labeled normal and abnormal image sequences of videos, are given and the foregrounds are segme
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發(fā)表于 2025-3-26 20:27:46 | 只看該作者
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