Assurant, Inc.

Nathan Breitsch

Stuart Saunders

Mircea Ionescu

Anthony Coble

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.

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

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New York, NY, United States of America

Nathan Breitsch