Samsung electronics co., ltd. (20240104410). METHOD AND DEVICE WITH CASCADED ITERATIVE PROCESSING OF DATA simplified abstract
Contents
- 1 METHOD AND DEVICE WITH CASCADED ITERATIVE PROCESSING OF DATA
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 METHOD AND DEVICE WITH CASCADED ITERATIVE PROCESSING OF DATA - 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
METHOD AND DEVICE WITH CASCADED ITERATIVE PROCESSING OF DATA
Organization Name
Inventor(s)
Changbeom Park of Suwon-si (KR)
METHOD AND DEVICE WITH CASCADED ITERATIVE PROCESSING OF DATA - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240104410 titled 'METHOD AND DEVICE WITH CASCADED ITERATIVE PROCESSING OF DATA
Simplified Explanation
The method and device disclosed in the patent application involve processing data through a sequence of tasks to improve the accuracy of predictions. Here are some key points to explain the innovation:
- Generating a target augmentation task sequence by processing the target data with a trained first model
- Generating augmented target data by performing data augmentation on the target data according to the target augmentation task sequence
- Obtaining a prediction result corresponding to the target data by inputting the augmented target data to a trained second model
Potential Applications
This technology could be applied in various fields such as image recognition, natural language processing, and speech recognition to enhance the accuracy of predictions.
Problems Solved
This technology addresses the challenge of improving prediction accuracy by utilizing data augmentation techniques in a systematic and efficient manner.
Benefits
The benefits of this technology include increased prediction accuracy, improved model performance, and enhanced overall efficiency in data processing tasks.
Potential Commercial Applications
This technology could be valuable in industries such as healthcare, finance, and e-commerce where accurate predictions are crucial for decision-making processes.
Possible Prior Art
One possible prior art in this field is the use of data augmentation techniques in machine learning models to improve prediction accuracy.
What are the specific data augmentation techniques used in this method?
The specific data augmentation techniques used in this method are not explicitly mentioned in the abstract.
How does the trained second model differ from the trained first model in terms of functionality?
The abstract does not provide details on how the trained second model differs from the trained first model in terms of functionality.
Original Abstract Submitted
disclosed is a method and device for processing data, and the method includes generating a target augmentation task sequence by processing the target data with a trained first model that performs inference on the target data to generate the target data augmentation task sequence, generate augmented target data by performing data augmentation on the target data according to the target augmentation task sequence, and obtaining a prediction result corresponding to the target data by inputting the augmented target data to a trained second model and performing a corresponding processing on the augmented target data by the trained second model.
