首页> 外国专利> LARGE MARGIN HIGH-ORDER DEEP LEARNING WITH AUXILIARY TASKS FOR VIDEO-BASED ANOMALY DETECTION

LARGE MARGIN HIGH-ORDER DEEP LEARNING WITH AUXILIARY TASKS FOR VIDEO-BASED ANOMALY DETECTION

机译:基于辅助异常任务的大型Margin高阶深度学习,用于基于视频的异常检测

摘要

A computer-implemented method and system are provided for video-based anomaly detection. The method includes forming, by a processor, a Deep High-Order Convolutional Neural Network (DHOCNN)-based model having a one-class Support Vector Machine (SVM) as a loss layer of the DHOCNN-based model. An objective of the SVM is configured to perform the video-based anomaly detection. The method further includes generating, by the processor, one or more predictions of an impending anomaly based on the high-order deep learning based model applied to an input image. The method also includes initiating, by the processor, an action to a hardware device to mitigate expected harm to at least one item selected from the group consisting of the hardware device, another hardware device related to the hardware device, and a person related to the hardware device.
机译:提供了一种用于基于视频的异常检测的计算机实现的方法和系统。该方法包括由处理器形成具有一类支持向量机(SVM)作为基于DHOCNN的模型的损失层的基于深度高阶卷积神经网络(DHOCNN)的模型。 SVM的目标配置为执行基于视频的异常检测。该方法还包括由处理器基于应用于输入图像的基于高阶深度学习的模型来生成即将发生的异常的一个或多个预测。该方法还包括由处理器发起对硬件设备的动作,以减轻对从由硬件设备,与该硬件设备相关的另一硬件设备以及与该硬件设备相关的人组成的组中选择的至少一项中的至少一项的预期伤害。硬件设备。

著录项

  • 公开/公告号US2017289409A1

    专利类型

  • 公开/公告日2017-10-05

    原文格式PDF

  • 申请/专利权人 NEC LABORATORIES AMERICA INC.;

    申请/专利号US201615380014

  • 发明设计人 RENQIANG MIN;DONGJIN SONG;ERIC COSATTO;

    申请日2016-12-15

  • 分类号H04N5/21;G06K9/46;G06K9/62;G06N3/04;G06N3/08;

  • 国家 US

  • 入库时间 2022-08-21 13:49:26

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