18574913. METHOD AND DEVICE FOR THE AUTOMATED CREATION OF A MACHINE LEARNING SYSTEM FOR MULTI-SENSOR DATA FUSION simplified abstract (Robert Bosch GmbH)
METHOD AND DEVICE FOR THE AUTOMATED CREATION OF A MACHINE LEARNING SYSTEM FOR MULTI-SENSOR DATA FUSION
Organization Name
Inventor(s)
Benedikt Sebastian Staffler of Muenchen (DE)
Jan Hendrik Metzen of Boeblingen (DE)
METHOD AND DEVICE FOR THE AUTOMATED CREATION OF A MACHINE LEARNING SYSTEM FOR MULTI-SENSOR DATA FUSION - A simplified explanation of the abstract
This abstract first appeared for US patent application 18574913 titled 'METHOD AND DEVICE FOR THE AUTOMATED CREATION OF A MACHINE LEARNING SYSTEM FOR MULTI-SENSOR DATA FUSION
The abstract describes a method for creating a machine learning system that can be configured for segmentation and object detection. The method involves selecting paths through a directed graph, including additional nodes from a subset, to find optimal input nodes for each output of the graph.
- The method involves providing a directed graph and selecting paths through it.
- Additional nodes are selected from a subset to optimize input nodes for each output.
- The goal is to create a machine learning system for segmentation and object detection.
Potential Applications: This technology could be used in various fields such as image recognition, autonomous vehicles, medical imaging, and surveillance systems.
Problems Solved: This method addresses the challenge of optimizing input nodes for segmentation and object detection tasks in machine learning systems.
Benefits: The technology can improve the accuracy and efficiency of segmentation and object detection processes, leading to better performance in various applications.
Commercial Applications: This technology could be valuable for companies developing products in the fields of computer vision, artificial intelligence, and automation.
Prior Art: Researchers and developers interested in this technology may want to explore prior art related to machine learning algorithms for segmentation and object detection tasks.
Frequently Updated Research: Stay informed about the latest advancements in machine learning algorithms for segmentation and object detection by following research publications and conferences in the field.
Questions about the technology: 1. How does this method improve the performance of segmentation and object detection tasks in machine learning systems? 2. What are the potential limitations or challenges of implementing this technology in real-world applications?
Original Abstract Submitted
A method for creating a machine learning system, which can be configured for segmentation and object detection. The method includes: providing a directed graph, selecting one or more paths through the graph, wherein at least one additional node is selected from a subset, and a path through the graph from an input node along the edges via the additional node to an output node is selected; finding the optimal input nodes from a plurality of input nodes for each output of the directed graph.
