首页> 外国专利> SYSTEM, METHOD, APPARATUS, AND COMPUTER PROGRAM PRODUCT FOR UTILIZING MACHINE LEARNING TO PROCESS AN IMAGE OF A MOBILE DEVICE TO DETERMINE A MOBILE DEVICE INTEGRITY STATUS

SYSTEM, METHOD, APPARATUS, AND COMPUTER PROGRAM PRODUCT FOR UTILIZING MACHINE LEARNING TO PROCESS AN IMAGE OF A MOBILE DEVICE TO DETERMINE A MOBILE DEVICE INTEGRITY STATUS

机译:用于利用机器学习的系统,方法,装置和计算机程序产品处理移动设备的图像以确定移动设备完整状态

摘要

A system, apparatus, method and computer program product are provided for determining a mobile device integrity status. Images of a mobile device captured by the mobile device and using a reflective surface are processed with various trained models, such as neural networks, to verify authenticity, detect damage, and to detect occlusions. A mask may be generated to enable identification of concave occlusions or blocked corners of an object, such as a mobile device, in an image. Images of the front and/or rear of a mobile device may be processed to determine the mobile device integrity status such as verified, not verified, or inconclusive. A user may be prompted to remove covers, remove occlusions, and/or move the mobile device closer to the reflective surface. A real-time response relating to the mobile device integrity status may be provided. The trained models may be trained to improve the accuracy of the mobile device integrity status.
机译:提供了一种用于确定移动设备完整性状态的系统,装置,方法和计算机程序产品。由移动设备捕获并使用反射表面捕获的移动设备的图像被处理有各种培训的型号,例如神经网络,以验证真实性,检测损坏,并检测闭塞。可以生成掩模以在图像中识别诸如移动设备的对象的凹形闭塞或阻塞角落。可以处理移动设备的前/或后部的图像以确定移动设备完整性状态,例如验证,不验证或不确定。可以提示用户删除盖子,删除遮挡,和/或将移动设备移动到更靠近反射表面。可以提供与移动设备完整性状态有关的实时响应。可以培训训练有素的模型以提高移动设备完整状态的准确性。

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