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