18478335. APPARATUS, METHOD, AND COMPUTER-READABLE MEDIUM FOR ROBUST RESPONSE TO ADVERSARIAL PERTURBATIONS USING HYPERDIMENSIONAL VECTORS simplified abstract (Intel Corporation)
Contents
- 1 APPARATUS, METHOD, AND COMPUTER-READABLE MEDIUM FOR ROBUST RESPONSE TO ADVERSARIAL PERTURBATIONS USING HYPERDIMENSIONAL VECTORS
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 APPARATUS, METHOD, AND COMPUTER-READABLE MEDIUM FOR ROBUST RESPONSE TO ADVERSARIAL PERTURBATIONS USING HYPERDIMENSIONAL VECTORS - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Original Abstract Submitted
APPARATUS, METHOD, AND COMPUTER-READABLE MEDIUM FOR ROBUST RESPONSE TO ADVERSARIAL PERTURBATIONS USING HYPERDIMENSIONAL VECTORS
Organization Name
Inventor(s)
Narayan Srinivasa of San Jose CA (US)
APPARATUS, METHOD, AND COMPUTER-READABLE MEDIUM FOR ROBUST RESPONSE TO ADVERSARIAL PERTURBATIONS USING HYPERDIMENSIONAL VECTORS - A simplified explanation of the abstract
This abstract first appeared for US patent application 18478335 titled 'APPARATUS, METHOD, AND COMPUTER-READABLE MEDIUM FOR ROBUST RESPONSE TO ADVERSARIAL PERTURBATIONS USING HYPERDIMENSIONAL VECTORS
Simplified Explanation
The abstract describes a patent application for a method and apparatus that assigns hyperdimensional vector values to locations and pixel intensity values in an image patch, ultimately generating a hyperdimensional representation patch value.
- Processor circuitry assigns location value HDV to a location in an image patch.
- At least a first channel HDV is assigned to the patch.
- Pixel intensity value HDVs are determined for each pixel in the patch.
- Pixel intensity value HDVs are bound together into at least one patch intensity value HDV.
- The first channel HDV and the patch intensity value HDV are bound together to produce a patch consensus intensity HDV.
- A first hyperdimensional representation patch value HDV is generated by binding together a combination of the patch consensus intensity HDV and the location value HDV.
Potential Applications
This technology could be applied in image processing, pattern recognition, and computer vision applications.
Problems Solved
This technology helps in efficiently representing and processing image patches in a hyperdimensional space.
Benefits
The benefits of this technology include improved image analysis, pattern recognition accuracy, and feature extraction capabilities.
Potential Commercial Applications
Potential commercial applications of this technology include image recognition systems, surveillance systems, and medical imaging software.
Possible Prior Art
There may be prior art related to hyperdimensional vector representation in image processing and computer vision applications.
Unanswered Questions
How does this technology compare to traditional image processing methods?
This article does not provide a direct comparison between this technology and traditional image processing methods. Further research or experimentation may be needed to determine the specific advantages and limitations of this approach.
What are the computational requirements for implementing this technology?
The abstract does not mention the computational resources needed to implement this technology. Understanding the computational demands of this method is crucial for practical applications and scalability.
Original Abstract Submitted
Apparatuses, methods, and articles of manufacture are disclosed. An example apparatus includes processor circuitry to assign a location value hyperdimensional vector (HDV) to a location in an image of a first patch of one or more pixels, assign at least a first channel HDV to the first patch, determine at least one pixel intensity value HDV for each of the one or more pixels in the first patch, bind together each of the pixel intensity value HDVs into at least one patch intensity value HDV, bind together the at least first channel HDV and the at least one patch intensity value HDV to produce a patch consensus intensity HDV, and generate a first hyperdimensional representation patch value HDV of the first patch by binding together at least a combination of the patch consensus intensity HDV and the location value HDV.
