Samsung electronics co., ltd. (20240161458). METHOD AND DEVICE WITH OBJECT CLASSIFICATION simplified abstract
Contents
- 1 METHOD AND DEVICE WITH OBJECT CLASSIFICATION
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 METHOD AND DEVICE WITH OBJECT CLASSIFICATION - 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 OBJECT CLASSIFICATION
Organization Name
Inventor(s)
METHOD AND DEVICE WITH OBJECT CLASSIFICATION - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240161458 titled 'METHOD AND DEVICE WITH OBJECT CLASSIFICATION
Simplified Explanation
The method described in the abstract involves generating a prediction consistency value to assess the consistency of predicting an object in an input image with respect to class prediction values from classification models. The class of the object is then identified based on the prediction consistency value and corresponding class prediction values from majority and minority class prediction models.
- Prediction consistency value is calculated to evaluate the accuracy of object prediction in an input image.
- The class of the object is determined based on whether it corresponds to a majority or minority class.
- Majority class prediction model is used to identify the class of the object if it corresponds to a majority class.
- Minority class prediction model is used to identify the class of the object if it corresponds to a minority class.
Potential Applications
This technology can be applied in image recognition systems, autonomous vehicles, medical imaging, and security systems for accurate object classification.
Problems Solved
This technology solves the problem of inconsistent object prediction in input images by utilizing prediction consistency values to determine the class of the object accurately.
Benefits
The benefits of this technology include improved object classification accuracy, enhanced performance of classification models, and increased reliability of prediction results.
Potential Commercial Applications
Potential commercial applications of this technology include integration into image recognition software, security systems, and autonomous vehicles for efficient object classification.
Possible Prior Art
One possible prior art could be the use of ensemble learning techniques in classification models to improve prediction accuracy.
What are the specific classification models used in this method?
The abstract does not specify the exact classification models used in the method. Further details on the specific models and their implementation would be beneficial for a comprehensive understanding of the technology.
How does the prediction consistency value impact the overall classification accuracy?
The abstract mentions that the prediction consistency value is used to determine the class of the object, but it does not elaborate on how this value influences the overall classification accuracy of the system. Further information on the relationship between prediction consistency and classification accuracy would provide valuable insights into the effectiveness of the method.
Original Abstract Submitted
disclosed is a method that includes generating a prediction consistency value that indicates a consistency of prediction of an object in an input image with respect to class prediction values for the object in an input image from classification models to which the input image is input, and identifying a class of the object. identifying the class of the object includes, in response to a class type being determined, based on the prediction consistency value, of the object being determined to correspond to a majority class, identifying a class of the object based on a corresponding class prediction value output for the object from a majority class prediction model, and in response to the class type of the object being determined to correspond to a minority class, identifying the class of the object based on another corresponding class prediction value output for the object from a minority class prediction model.