17989831. METHOD, ELECTRONIC DEVICE AND COMPUTER PROGRAM PRODUCT FOR DATA PROCESSING simplified abstract (Dell Products L.P.)
Contents
- 1 METHOD, ELECTRONIC DEVICE AND COMPUTER PROGRAM PRODUCT FOR DATA PROCESSING
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 METHOD, ELECTRONIC DEVICE AND COMPUTER PROGRAM PRODUCT FOR DATA PROCESSING - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Key Features and Innovation
- 1.6 Potential Applications
- 1.7 Problems Solved
- 1.8 Benefits
- 1.9 Commercial Applications
- 1.10 Prior Art
- 1.11 Frequently Updated Research
- 1.12 Questions about Data Processing Technology
- 1.13 Original Abstract Submitted
METHOD, ELECTRONIC DEVICE AND COMPUTER PROGRAM PRODUCT FOR DATA PROCESSING
Organization Name
Inventor(s)
METHOD, ELECTRONIC DEVICE AND COMPUTER PROGRAM PRODUCT FOR DATA PROCESSING - A simplified explanation of the abstract
This abstract first appeared for US patent application 17989831 titled 'METHOD, ELECTRONIC DEVICE AND COMPUTER PROGRAM PRODUCT FOR DATA PROCESSING
Simplified Explanation
The patent application describes a method for data processing that involves training a text-image association model using image and text inputs, along with corresponding feature codebooks, to implement data processing based on the association between the image and text inputs.
- Acquiring an image input and text input pair
- Obtaining image and text feature codebooks
- Training a text-image association model
- Implementing data processing based on the learned association
Key Features and Innovation
- Training a model to learn associations between image and text inputs
- Using feature codebooks to facilitate data processing
- Implementing data compression or retrieval based on the learned associations
Potential Applications
This technology can be applied in various fields such as image recognition, natural language processing, data compression, and data retrieval systems.
Problems Solved
This technology addresses the challenge of efficiently processing data by learning associations between different types of inputs, leading to improved data processing capabilities.
Benefits
- Enhanced data processing efficiency
- Improved accuracy in data retrieval and compression
- Facilitates seamless integration of image and text data
Commercial Applications
- Image recognition software
- Natural language processing tools
- Data compression algorithms
- Data retrieval systems
Prior Art
Information on prior art related to this technology is not provided in the abstract.
Frequently Updated Research
There is no information on frequently updated research relevant to this technology.
Questions about Data Processing Technology
How does the text-image association model improve data processing efficiency?
The text-image association model enhances data processing efficiency by learning associations between image and text inputs, allowing for more accurate and streamlined data processing.
What are the potential real-world applications of this technology beyond data processing?
The technology can be applied in various fields such as image recognition, natural language processing, and data compression, expanding its utility beyond traditional data processing tasks.
Original Abstract Submitted
Embodiments of the present disclosure provide a method, an electronic device, and a computer program product for data processing. A method for data processing includes acquiring an image input and text input pair, the image input and text input pair comprising image input and text input, obtaining an image feature codebook corresponding to the image input and a text feature codebook corresponding to the text input, and training a text-image association model by using the image feature codebook and the text feature codebook, the text-image association model implementing the data processing based on the association between the image input and the text input. For example, a model may be adopted to learn an association between an image feature codebook corresponding to image input and a text feature codebook corresponding to text input, and data processing, such as data compression or data retrieval, is implemented using the learned association.
