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Object detection in image based on stochastic optimization

机译:基于随机优化的图像目标检测

摘要

An electronic device includes circuitry that determines probability map information for a first image, based on application of a neural network model on the first image. The neural network model is trained to detect one or more objects based on a plurality of images associated with the one or more objects. The probability map information indicates a probability value for each pixel in the first image. A region corresponding to the one or more objects is detected in the first image based on the probability map information. A first set of sub-images is determined from the detected region, based on application of a stochastic optimization function on the probability map information. The one or more objects are detected from a second set of sub-images of the first set of sub-images, based on application of the neural network model on the second set of sub-images.
机译:一种电子装置,包括基于对第一图像应用神经网络模型来确定第一图像的概率映射信息的电路。训练神经网络模型以基于与一个或多个对象相关联的多个图像来检测一个或多个对象。概率图信息指示第一图像中每个像素的概率值。基于概率图信息在第一图像中检测与一个或多个对象相对应的区域。基于对概率图信息应用随机优化函数,从检测到的区域确定第一组子图像。基于对第二组子图像应用神经网络模型,从第一组子图像的第二组子图像检测一个或多个对象。

著录项

  • 公开/公告号US11288507B2

    专利类型

  • 公开/公告日2022-03-29

    原文格式PDF

  • 申请/专利权人 SONY CORPORATION;

    申请/专利号US201916585538

  • 申请日2019-09-27

  • 分类号G06K9;G06K9/32;G06N3/08;

  • 国家 US

  • 入库时间 2022-08-25 00:08:47

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