Samsung electronics co., ltd. (20240135587). METHOD OF LEARNING PARAMETER OF SENSOR FILTER AND APPARATUS FOR PERFORMING THE SAME simplified abstract
Contents
- 1 METHOD OF LEARNING PARAMETER OF SENSOR FILTER AND APPARATUS FOR PERFORMING THE SAME
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 METHOD OF LEARNING PARAMETER OF SENSOR FILTER AND APPARATUS FOR PERFORMING THE SAME - 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 Unanswered Questions
- 1.11 Original Abstract Submitted
METHOD OF LEARNING PARAMETER OF SENSOR FILTER AND APPARATUS FOR PERFORMING THE SAME
Organization Name
Inventor(s)
Sung Kwang Cho of Suwon-si (KR)
Dong Kyung Nam of Suwon-si (KR)
METHOD OF LEARNING PARAMETER OF SENSOR FILTER AND APPARATUS FOR PERFORMING THE SAME - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240135587 titled 'METHOD OF LEARNING PARAMETER OF SENSOR FILTER AND APPARATUS FOR PERFORMING THE SAME
Simplified Explanation
The abstract describes a method of learning a parameter of a sensor filter through simulations and vision models.
- The method involves performing simulations on a target image for each spectrum of a sensor filter.
- Output values are obtained by inputting the simulated image to a vision model for a vision task.
- The parameter of the sensor filter is learned based on the loss between the label of the vision model and the output value of the vision model.
Potential Applications
This technology could be applied in various fields such as image processing, computer vision, and sensor technology.
Problems Solved
This technology helps in optimizing sensor filters for better performance and accuracy in vision tasks.
Benefits
The benefits of this technology include improved sensor filter parameters, enhanced vision model accuracy, and overall better performance in vision tasks.
Potential Commercial Applications
Potential commercial applications of this technology include use in surveillance systems, autonomous vehicles, medical imaging, and industrial automation.
Possible Prior Art
One possible prior art could be the use of machine learning algorithms to optimize sensor filters in vision tasks.
Unanswered Questions
How does this method compare to traditional methods of optimizing sensor filters?
This article does not provide a direct comparison to traditional methods of optimizing sensor filters.
What are the limitations of this method in real-world applications?
The article does not address the potential limitations of implementing this method in practical, real-world scenarios.
Original Abstract Submitted
a method of learning a parameter of a sensor filter and an apparatus for performing the method are provided. the learning method may include performing a simulation on a target image for each spectrum of a sensor filter, obtaining an output value by inputting the simulated image to a vision model for a vision task, and learning a parameter of the sensor filter based on a loss between a label of the vision model and the output value of the vision model.
