18298526. SHAPE DETECTION TRANSFORMATION USING MEMRISTIVE IN-MEMORY COMPUTING simplified abstract (International Business Machines Corporation)

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SHAPE DETECTION TRANSFORMATION USING MEMRISTIVE IN-MEMORY COMPUTING

Organization Name

International Business Machines Corporation

Inventor(s)

Ghazi Sarwat Syed of Kilchberg (CH)

SHAPE DETECTION TRANSFORMATION USING MEMRISTIVE IN-MEMORY COMPUTING - A simplified explanation of the abstract

This abstract first appeared for US patent application 18298526 titled 'SHAPE DETECTION TRANSFORMATION USING MEMRISTIVE IN-MEMORY COMPUTING

Simplified Explanation: The patent application describes a method for implementing shape detection transformation using a memristive computing crossbar array.

Key Features and Innovation:

  • Utilizes a crossbar array tile for parametric space transformation.
  • Input data in vectorized form from an image is used for the transformation.
  • Accumulation operation is performed using the output of the first crossbar array tile.
  • Shape tracing operation is carried out using the output of the second crossbar array tile.
  • Output of the third crossbar array determines parameter values of the detected shape.

Potential Applications: This technology can be applied in image processing, pattern recognition, and computer vision systems.

Problems Solved: Addresses the need for efficient shape detection and transformation in computational memory systems.

Benefits:

  • Improved accuracy in shape detection.
  • Faster processing of image data.
  • Enhanced performance in pattern recognition tasks.

Commercial Applications: The technology can be utilized in security systems, medical imaging, and industrial automation for enhanced shape detection and analysis capabilities.

Prior Art: Prior research in memristive computing and crossbar arrays can provide insights into similar applications and advancements in the field.

Frequently Updated Research: Stay updated on the latest developments in memristive computing, crossbar arrays, and shape detection algorithms for potential improvements in the technology.

Questions about Shape Detection Transformation: 1. How does the integration of memristive computing enhance shape detection accuracy? 2. What are the implications of using crossbar arrays for shape tracing operations?


Original Abstract Submitted

A method for a computational memory implementing a shape detection transformation using an integrated memristive computing crossbar array is disclosed. The method comprises using a first crossbar array tile of at least three crossbar tiles of a memristive computing crossbar array for a parametric space transformation of the shape detection transformation, wherein data of an image in a vectorized form is used as input for the first crossbar array, using an output of the first crossbar array tile as input for a second crossbar array tile for an accumulation operation of the shape detection transformation, and using an output of the second crossbar array tile as input for a third crossbar array tile for a shape tracing operation of the transformation, such that an output of the third crossbar array determines parameter values of a detected shape.

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