18156017. DATA MINING USING MACHINE LEARNING FOR AUTONOMOUS SYSTEMS AND APPLICATIONS simplified abstract (NVIDIA Corporation)
Contents
DATA MINING USING MACHINE LEARNING FOR AUTONOMOUS SYSTEMS AND APPLICATIONS
Organization Name
Inventor(s)
Ryan Marc Christian Benkert of Atlanta GA (US)
Shanshan Xu of Palo Alto CA (US)
DATA MINING USING MACHINE LEARNING FOR AUTONOMOUS SYSTEMS AND APPLICATIONS - A simplified explanation of the abstract
This abstract first appeared for US patent application 18156017 titled 'DATA MINING USING MACHINE LEARNING FOR AUTONOMOUS SYSTEMS AND APPLICATIONS
Simplified Explanation: This patent application describes the use of neural networks in machine learning data mining processes for autonomous or semi-autonomous systems and applications. The neural networks are utilized to classify and process input data to determine object classifications and uncertainty classifications.
Key Features and Innovation:
- Utilization of neural networks for data mining processes in autonomous systems.
- Classification of input data using multiple neural networks to determine object classifications and uncertainty classifications.
Potential Applications: The technology can be applied in various fields such as autonomous vehicles, robotics, image recognition, and natural language processing.
Problems Solved: The technology addresses the need for efficient and accurate data mining processes in autonomous or semi-autonomous systems.
Benefits:
- Improved accuracy in object classification.
- Enhanced efficiency in data mining processes.
- Increased reliability in autonomous systems.
Commercial Applications: Potential commercial applications include autonomous vehicles, surveillance systems, medical imaging analysis, and industrial automation.
Prior Art: Readers can explore prior research on neural networks in data mining processes, machine learning applications, and autonomous systems.
Frequently Updated Research: Stay updated on advancements in neural network technology, machine learning algorithms, and data mining techniques for autonomous systems.
Questions about Neural Networks in Data Mining: 1. How do neural networks improve the accuracy of object classification in data mining processes? 2. What are the potential challenges in implementing neural networks for uncertainty classifications in autonomous systems?
Original Abstract Submitted
In various examples, machine learning data mining for autonomous or semi-autonomous systems and applications is described herein. Systems and methods are disclosed that use neural networks to perform one or more data mining processes. For instance, a first neural network(s) may process input data (e.g., image data) to remove data samples (e.g., images) that are associated with a first object classification(s) and/or a second neural network(s) may process the input data to retrieve data samples (e.g., images) that are associated with a second classification(s). Next, a third neural network(s) may process filtered input data (e.g., the input data not removed by the first neural network(s) and/or the input data retrieved by the second neural network(s)) to determine uncertainty classifications associated with the data samples and a fourth neural network(s) may process the filtered input data to determine final object classifications associated with the data samples.
