• If we don't want to wait in line before the checkout counters, we can use Toshiba's new object recognition scanner.

    如果我们不想在收银台前排队,我们可以使用东芝新的物体识别扫描仪。

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  • Tips for better test object recognition.

    更好测试对象识别的建议。

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  • Choose the correct object recognition method.

    选择合适的对象识别方法。

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  • This allows for more flexibility in object recognition.

    这允许对象识别中的更多灵活性。

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  • The method can also be employed in other fields of object recognition.

    这种评价方法还可以被推广到目标识别的其它领域。

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  • The recognition of airplane is one of the applications of object recognition.

    飞机机型的识别属于目标识别的一个具体应用。

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  • Detection of echo signal is an important part of underwater object recognition.

    水下目标回声信号的检测是主动声纳目标识别的重要内容。

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  • The ObjectFactory class addresses this issue with dynamic object recognition methods.

    ObjectFactory 类用动态对象识别方法解决了这个问题。

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  • Mounted on the glasses is a tiny camera, display screen and object recognition system.

    这种眼镜中装置了微型摄像头、显示屏以及物体识别系统。

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  • In the system of IR object recognition, it is needed to collect IR image data in realtime.

    红外目标识别系统中,需要实时采集红外传感器的图像数据。

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  • The viewpoint has been the focus of the debates in many recent object recognition studies.

    视点问题是物体识别研究中的热点问题。

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  • The three-dimensional object recognition is an important topic in computer vision research.

    三维物体识别是计算机视觉研究的一项重要课题。

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  • Graph matching RRWM method. Graph matching can be used for object recognition, pattern recognition.

    说明:图匹配的RRWM方法。图匹配可用于目标识别,模式识别。

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  • Script recording will be generic, in that object recognition will be as ATL or HTML objects, not as Siebel objects.

    脚本记录将会产生,这样的话对象将作为ATL或者HTML对象被识别,而不是Siebel 对象。

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  • Vision is the best perception system of human. Vision invariants for planar object recognition catch our attention.

    视觉是人类最完善的感知系统,基于视觉不变量的平面目标识别方法近年来得到广泛的关注。

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  • A realtime dynamic object recognition and localization method is presented for mobile robot using binocular vision.

    提出了一种双目移动机器人实时动态目标识别与定位方法。

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  • Experimental results show that the approach presented has ideal precision and speediness for color object recognition.

    实验结果表明该方法具有较理想的彩色目标识别精度和实时性。

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  • The system has significant practice value of the object recognition, atmosphere supervising and laser cooling of atoms etc.

    该系统在目标识别、大气环境监测、激光冷却原子等应用中具有重要的价值。

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  • Based on the Discrete Fractal Brownian Random Field (DFBR) an algorithm of multiresolution object recognition is presented.

    在离散分形布朗随机场(DFBR)理论的基础上,提出一种多分辨率目标识别算法。

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  • In this paper a method of the three-dimensional object recognition with rotation-invariant based on moire fringe is proposed.

    本文提出一种基于莫尔条纹的三维物体旋转不变识别方法。

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  • Often, we find that each new build of our application under test changes our object recognition properties enough that our automation breaks.

    我们常常发现,在测试中,每次构建新的应用程序,对象识别属性的更改都很大,以致于破坏了自动化。

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  • Technest\'s 3D sensing algorithm fuses data from multiple sensors to achieve high-resolution rapid 3D mapping and reliable object recognition.

    该公司的3D算法能够从多个传感器融合数据,实现高清快速3D制图和可靠的目标识别。

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  • An object recognition and localization algorithm based on local feature-turning Angle between neighbouring tangent vectors, is presented.

    提出了基于切矢转角局部特征的目标识别与定位算法。

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  • The neural net is suited for computing two dimensional image moments in real time and it is further applicable to image or object recognition.

    该网络适合于实时计算二维图象矩,可进一步用于图象或目标识别。

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  • Technique of three-dimensional object recognition is one of the most important techniques in video tracking system and also a difficult problem in it.

    三维目标识别技术是电视跟踪系统中的关键技术之一,也是目前该领域亟待解决的一个难题。

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  • The face motion could be estimated by using face skin color model integrated with feature based object recognition technique and extended Kalman filter.

    以人脸肤色模型为基础,结合目标形状特征识别方法,并用扩展卡尔曼滤波估计目标运动轨迹,实现基于肤色的人脸实时跟踪鲁棒方法。

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  • Image segmentation is significant because all subsequent tasks such as feature extraction, object recognition are dependent on the quality of image segmentation.

    图像在分割后的处理,如特征提取、目标识别等都依赖于图像的分割质量,因此具有十分重要的意义。

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  • Image segmentation is significant because all subsequent tasks such as feature extraction, object recognition are dependent on the quality of image segmentation.

    图像在分割后的处理,如特征提取、目标识别等都依赖于图像的分割质量,因此具有十分重要的意义。

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