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A semi-supervised learning framework based on spatio-temporal semantic events for maritime anomaly detection and behavior analysis

机译：基于时空语义事件的半监督学习框架，用于海洋异常检测和行为分析

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International audience

机译：国际观众

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Vandecasteele Arnaud; Devillers Rodolphe; Napoli Aldo;
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年度 2013
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正文语种 en
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1. A semi-supervised incremental learning method based on adaptive probabilistic hypergraph for video semantic detection [J] . Zhan Yongzhao, Sun Jiayao, Niu Dejiao, Multimedia Tools and Applications . 2015,第15期

机译：基于自适应概率超图的视频语义检测半监督增量学习方法
2. A framework for anomaly detection in maritime trajectory behavior [J] . Lei Po-Ruey Knowledge and information systems . 2016,第1期

机译：海洋轨迹行为异常检测的框架
3. Highly-Efficient and Automatic Spectrum Inspection Based on AutoEncoder and Semi-Supervised Learning for Anomaly Detection in EONs [J] . Liu Siqi, Kong Jiawei, Pan Xiaoqin, Journal of Lightwave Technology . 2021,第5期

机译：基于AutoEncoder的高效和自动频谱检测和半监督对eons异常检测的半监督学习
4. A HMM BASED SEMANTIC ANALYSIS FRAMEWORK FOR SPORTS GAME EVENT DETECTION [C] . Gu Xu, Yu-Fei Ma, Hong-Jiang Zhang, IEEE International Conference on Image Processing . 2003

机译：基于HMM的运动游戏事件检测语义分析框架
5. A spatio-temporal data representation framework with applications to anomaly detection in the maritime domain [D] . Avram, Vladimir Radu. 2012

机译：具有应用于海洋域中的异常检测的时空数据表示框架
6. Anomalous Behavior Detection Framework Using HTM-Based Semantic Folding Technique [O] . Hamid Masood Khan, Fazal Masud Khan, Aurangzeb Khan, 2021

机译：基于HTM的语义折叠技术的异常行为检测框架
7. A spatio-temporal data representation framework with applications to anomaly detection in the maritime domain [O] . Avram Vladimir Radu 2012

机译：时空数据表示框架及其在海域异常检测中的应用

A semi-supervised learning framework based on spatio-temporal semantic events for maritime anomaly detection and behavior analysis

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