International business machines corporation (20240185079). SEMI-SUPERVISED SIMILARITY-BASED CLUSTERING IN RESOURCE EVALUATION simplified abstract
Contents
- 1 SEMI-SUPERVISED SIMILARITY-BASED CLUSTERING IN RESOURCE EVALUATION
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 SEMI-SUPERVISED SIMILARITY-BASED CLUSTERING IN RESOURCE EVALUATION - 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
SEMI-SUPERVISED SIMILARITY-BASED CLUSTERING IN RESOURCE EVALUATION
Organization Name
international business machines corporation
Inventor(s)
Yash Vardhan Singh of Bangalore (IN)
Khushboo Tak of Bangalore (IN)
Parmar Yogeshbhai of Gujarat (IN)
SEMI-SUPERVISED SIMILARITY-BASED CLUSTERING IN RESOURCE EVALUATION - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240185079 titled 'SEMI-SUPERVISED SIMILARITY-BASED CLUSTERING IN RESOURCE EVALUATION
Simplified Explanation
The patent application describes a method for determining the authenticity of resources using similarity-based clustering of resource images.
- Image embeddings are generated for resource images, including known authentic and known counterfeit resources.
- Similarity-based clustering processes identify outlier embeddings in the embedding space to determine authenticity.
- Outlier embeddings for counterfeit resource images are used to create new clusters representing previously unrecognized counterfeit resources.
Potential Applications
This technology could be applied in industries where counterfeit detection is crucial, such as luxury goods, pharmaceuticals, and electronics.
Problems Solved
This technology addresses the issue of identifying counterfeit resources that may otherwise go undetected, protecting consumers and brand reputation.
Benefits
The method provides a holistic approach to resource authenticity determination, leveraging image embeddings and clustering for accurate results.
Potential Commercial Applications
Commercial applications include anti-counterfeiting solutions for brands, authentication services for online marketplaces, and quality control in manufacturing processes.
Possible Prior Art
One possible prior art could be the use of image recognition technology for counterfeit detection in various industries.
What is the accuracy rate of this method in determining resource authenticity?
The accuracy rate of this method in determining resource authenticity will depend on the quality of the image embeddings and the effectiveness of the similarity-based clustering algorithms used.
How scalable is this technology for large-scale counterfeit detection operations?
The scalability of this technology for large-scale counterfeit detection operations will depend on the computational resources available and the efficiency of the clustering processes in handling a high volume of resource images.
Original Abstract Submitted
a holistic approach to determining resource authenticity using similarity-based clustering of resource images. resource images are input to generate image embeddings for an embedding space including generated embeddings for known authentic and known counterfeit resources. similarity-based clustering processes identify outlier embeddings in the embedding space for determination of authenticity. a set of outlier embeddings for counterfeit resource images is the basis for creating new clusters representing previously unrecognized counterfeit resources.
