20240022407. METHOD AND SYSTEM MODELS FOR DIGITAL OBJECT GENERATION simplified abstract (Emoji ID, LLC)

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METHOD AND SYSTEM MODELS FOR DIGITAL OBJECT GENERATION

Organization Name

Emoji ID, LLC

Inventor(s)

Naveen Kumar Jain of Nashville TN (US)

Riccardo Paolo Spagni of Plettenburg (ZA)

METHOD AND SYSTEM MODELS FOR DIGITAL OBJECT GENERATION - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240022407 titled 'METHOD AND SYSTEM MODELS FOR DIGITAL OBJECT GENERATION

Simplified Explanation

The disclosed patent application describes models used in digital object generation systems and methods. These models receive input data and recognize elements of the data for use in generating digital objects. The models learn to recognize the data and its features by comparing normalized vectors of the input data and parameters. They can learn from extracted features or directly from the input data. The models identify features of the data based on distinctiveness, interoperability, or exclusivity features in the received data. The output of the models for digital object generation includes an amalgamation of recognized or extracted features from the input data.

  • Models used in digital object generation systems and methods
  • Models receive input data and recognize elements of the data
  • Models learn to recognize the data and its features by comparing normalized vectors
  • Models can learn from extracted features or directly from the input data
  • Models identify features of the data based on distinctiveness, interoperability, or exclusivity features
  • Output of the models includes an amalgamation of recognized or extracted features from the input data

Potential Applications

  • Digital content creation
  • Image and video editing
  • Virtual reality and augmented reality experiences
  • Computer-generated graphics and animations

Problems Solved

  • Efficient recognition and extraction of features from input data
  • Improved digital object generation by utilizing distinctiveness, interoperability, or exclusivity features
  • Streamlining the process of creating digital objects

Benefits

  • Enhanced accuracy and efficiency in digital object generation
  • Increased creativity and customization options for digital content creation
  • Improved user experience in virtual reality and augmented reality applications
  • Time and cost savings in computer-generated graphics and animations.


Original Abstract Submitted

disclosed herein are models used in digital object generation systems and methods. the models receive input data recognize elements of the received data for use in digital object generation. the models learn to recognize the data and features thereof by comparing normalized vectors of the received data and parameters. the models learn from extracted features of the input data or from the input data directly. the models identify features of the data for use in digital object generation based on distinctiveness, interoperability, or exclusivity features in the received data. the models provide an output for digital object generation that includes an amalgamation of features, recognized or extracted from the received data.

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