18547605. METHOD FOR FUSING MEASUREMENT DATA CAPTURED USING DIFFERENT MEASUREMENT MODALITIES simplified abstract (Robert Bosch GmbH)
Contents
- 1 METHOD FOR FUSING MEASUREMENT DATA CAPTURED USING DIFFERENT MEASUREMENT MODALITIES
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 METHOD FOR FUSING MEASUREMENT DATA CAPTURED USING DIFFERENT MEASUREMENT MODALITIES - 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 the Technology
- 1.13 Original Abstract Submitted
METHOD FOR FUSING MEASUREMENT DATA CAPTURED USING DIFFERENT MEASUREMENT MODALITIES
Organization Name
Inventor(s)
Balint Szollosi-nagy of Budapest (HU)
Ernest-Adrian Scheiber of Budapest (HU)
Zoltan Karasz of Budapest (HU)
METHOD FOR FUSING MEASUREMENT DATA CAPTURED USING DIFFERENT MEASUREMENT MODALITIES - A simplified explanation of the abstract
This abstract first appeared for US patent application 18547605 titled 'METHOD FOR FUSING MEASUREMENT DATA CAPTURED USING DIFFERENT MEASUREMENT MODALITIES
Simplified Explanation
This patent application describes a method for combining data from two different measurements by modifying latent representations of features.
Key Features and Innovation
- Determining latent representations of features from two sets of measurement data.
- Decoding information about features from the latent representations.
- Modifying features in one latent representation based on the other.
- Updating and decoding information about features from the modified latent representations.
Potential Applications
This technology could be applied in various fields such as image processing, data analysis, and pattern recognition.
Problems Solved
This method addresses the challenge of integrating data from multiple sources to improve the accuracy and reliability of feature representation.
Benefits
The benefits of this technology include enhanced data fusion capabilities, improved feature extraction, and increased accuracy in data analysis.
Commercial Applications
- Image recognition systems
- Data mining software
- Biometric identification technology
Prior Art
Researchers can explore prior art related to latent feature representation, data fusion techniques, and machine learning algorithms.
Frequently Updated Research
Stay informed about the latest advancements in data fusion, feature extraction, and machine learning techniques to enhance the application of this technology.
Questions about the Technology
How does this method improve feature representation compared to traditional data fusion techniques?
This method enhances feature representation by modifying latent representations based on information from multiple measurements, leading to more accurate and comprehensive feature extraction.
What are the potential limitations of using this technology in real-world applications?
The limitations may include computational complexity, data compatibility issues, and the need for large datasets to train the model effectively.
Original Abstract Submitted
A method for fusing first measurement data. The method include: determining a first latent representation of features from the first measurement data; decoding first information about features from the first latent representation; determining a second latent representation of features from the second measurement data; decoding second information about features from the second latent representation; modifying features in the first latent representation based on features in the second latent representation; modifying features in the second latent representation based on features in the first latent representation; decoding updated information about features from the updated first latent representation; and decoding updated information about features from the updated second latent representation.
