20240037910. Quantum Method and System for Classifying Images simplified abstract (Multiverse Computing S.L.)

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Quantum Method and System for Classifying Images

Organization Name

Multiverse Computing S.L.

Inventor(s)

Victor Onofre of DONOSTIA / SAN SEBASTIÁN (ES)

[[:Category:Daniel Garc�a of DONOSTIA / SAN SEBASTIÁN (ES)|Daniel Garc�a of DONOSTIA / SAN SEBASTIÁN (ES)]][[Category:Daniel Garc�a of DONOSTIA / SAN SEBASTIÁN (ES)]]

[[:Category:Román Or�s of DONOSTIA / SAN SEBASTIÁN (ES)|Román Or�s of DONOSTIA / SAN SEBASTIÁN (ES)]][[Category:Román Or�s of DONOSTIA / SAN SEBASTIÁN (ES)]]

Quantum Method and System for Classifying Images - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240037910 titled 'Quantum Method and System for Classifying Images

Simplified Explanation

The abstract describes a computer-implemented method for classifying images using a quantum trained vision system. The method involves enhancing the contrast of the image and applying dimension reduction to the contrast-enhanced image. The enhanced and dimensionally reduced image is then passed to a quantum trained vision system, which generates a result. The result can be a binary yes/no or true/false indication of whether the image falls into a predefined class or an indication of an object in the image.

  • The method involves enhancing the contrast of an image.
  • Dimension reduction is applied to the contrast-enhanced image.
  • The enhanced and dimensionally reduced image is passed to a quantum trained vision system.
  • The quantum trained vision system generates a result.
  • The result can be a binary indication of whether the image falls into a predefined class.
  • The result can also indicate the presence of an object in the image.

Potential applications of this technology:

  • Image classification in various fields such as medical imaging, surveillance, and autonomous vehicles.
  • Object detection and recognition in computer vision systems.
  • Quality control and inspection in manufacturing processes.
  • Facial recognition and biometric identification systems.

Problems solved by this technology:

  • Improved accuracy and efficiency in image classification and object detection tasks.
  • Overcoming limitations of traditional image processing techniques.
  • Handling large and complex datasets.
  • Enabling real-time decision-making based on image analysis.

Benefits of this technology:

  • Enhanced image contrast improves the visibility of objects and details.
  • Dimension reduction reduces the computational complexity and memory requirements.
  • Quantum trained vision system offers potential for improved accuracy and performance.
  • Enables automated and intelligent systems capable of analyzing and interpreting images.


Original Abstract Submitted

a computer-implemented method of classifying an image using a quantum trained vision system. the method comprises enhancing contrast of the image and applying dimension reduction to the contrast-enhance image. the enhanced contrast and dimensionally reduced image is passed to a quantum trained vision system and a result is generated from the quantum trained vision system. the result could be a simply yes/no or true/false binary result to see whether the image fell into one of several predefined classes. alternatively, the result could be an indication of an object in the image.

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