18134328. METHOD OF LEARNING PARAMETER OF SENSOR FILTER AND APPARATUS FOR PERFORMING THE SAME simplified abstract (SAMSUNG ELECTRONICS CO., LTD.)
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 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 18134328 titled 'METHOD OF LEARNING PARAMETER OF SENSOR FILTER AND APPARATUS FOR PERFORMING THE SAME
Simplified Explanation
The abstract describes a method for learning a parameter of a sensor filter by simulating images, inputting them into a vision model, and adjusting the filter based on the model's output.
- Simulation performed on target image for each spectrum of sensor filter
- Output value obtained by inputting simulated image to vision model for a vision task
- Parameter of sensor filter learned based on loss between vision model label and output value
Potential Applications
This technology could be applied in various fields such as:
- Image processing
- Computer vision
- Machine learning
Problems Solved
This technology helps in:
- Improving the accuracy of sensor filters
- Enhancing the performance of vision models
- Optimizing image processing tasks
Benefits
The benefits of this technology include:
- Increased efficiency in image analysis
- Enhanced quality of vision tasks
- Improved overall performance of sensor filters
Potential Commercial Applications
With its applications in image processing and computer vision, this technology could be utilized in:
- Surveillance systems
- Medical imaging devices
- Autonomous vehicles
Possible Prior Art
One possible prior art could be the use of machine learning algorithms to optimize sensor filters in image processing tasks. Another could be the simulation of images to improve the performance of vision models.
What is the impact of this technology on the field of computer vision?
This technology could potentially revolutionize the field of computer vision by enhancing the accuracy and efficiency of sensor filters, leading to improved performance in various vision tasks.
How does this method compare to traditional approaches in sensor filter optimization?
This method offers a more systematic and data-driven approach to learning sensor filter parameters compared to traditional methods, which may rely more on manual tuning and heuristics.
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.
