Automated image detection utilizing a convolutional XGBoost image recognition machine learning model on edge computing with blockchain mobile authentication

US12412384B2 · kind B2 · utility

Assignee

• Bank of America Corporation · US

Inventors

• Elvis Nyamwange · Little Elm, US
• Sailesh Vezzu
• Amer Ali · Jersey City, US
• Rahul Shashidhar Phadnis · Charlotte, US
• Rahul Yaksh · Austin, US
• Hari Vuppala · Concord, US
• Pratap Dande · Pomona Park, US
• Brian Neal Jacobson · Los Angeles, US
• Erik Dahl · Nonatum Mills, US

Key dates

• Filing date: Jul 28, 2023
• Grant date: Sep 9, 2025
• Expiry date: Jun 4, 2044

Classification

• Technology area (CPC G): Physics
• CPC primary: G06V20/48
• WIPO field: Computer technology
• WIPO sector: Electrical engineering

Abstract

An apparatus may include conduction of a secure transfer at a point of identification using image recognition and blockchain authentication. The apparatus may include a computer processor, a camera, an image capturing machine, a reference database, an XGBoost image recognition machine learning model, and a blockchain. The computer processor may be an edge computing device. The computer processor may be configured to identify a user at a point of identification by capturing an image, running the Features detection engine to identify sets of features, running the XGBoost image recognition machine learning model to identify labels in the sets of features, and matching the sets of features and labels to a record in the reference database. The computer processor may further be configured to seek user approval on the user's portable device before providing the transfer. Once the user has approved the transfer, the transfer may be recorded in the blockchain.