18649088. POINT CLOUD DATA PROCESSING METHOD, NEURAL NETWORK TRAINING METHOD, AND RELATED DEVICE simplified abstract (Huawei Technologies Co., Ltd.)
Contents
- 1 POINT CLOUD DATA PROCESSING METHOD, NEURAL NETWORK TRAINING METHOD, AND RELATED DEVICE
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 POINT CLOUD DATA PROCESSING METHOD, NEURAL NETWORK TRAINING METHOD, AND RELATED DEVICE - 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 Point Cloud Data Processing
- 1.13 Original Abstract Submitted
POINT CLOUD DATA PROCESSING METHOD, NEURAL NETWORK TRAINING METHOD, AND RELATED DEVICE
Organization Name
Inventor(s)
POINT CLOUD DATA PROCESSING METHOD, NEURAL NETWORK TRAINING METHOD, AND RELATED DEVICE - A simplified explanation of the abstract
This abstract first appeared for US patent application 18649088 titled 'POINT CLOUD DATA PROCESSING METHOD, NEURAL NETWORK TRAINING METHOD, AND RELATED DEVICE
Simplified Explanation
The patent application describes a method for processing point cloud data using neural networks in the field of artificial intelligence.
Key Features and Innovation
- Obtaining point cloud data and dividing it into target cubes.
- Generating initial features for each cube based on target points.
- Updating features using an attention mechanism.
- Performing feature processing to predict results.
Potential Applications
This technology can be used in various industries such as autonomous vehicles, robotics, augmented reality, and environmental monitoring.
Problems Solved
This method addresses the challenge of efficiently processing large amounts of point cloud data to extract meaningful information.
Benefits
The method allows for accurate prediction results from complex point cloud data, enabling better decision-making in various applications.
Commercial Applications
- Autonomous vehicles for improved navigation and obstacle detection.
- Robotics for enhanced object recognition and manipulation.
- Augmented reality for realistic virtual environments.
- Environmental monitoring for analyzing terrain and vegetation.
Prior Art
Researchers can explore prior art related to point cloud data processing, neural networks, and feature extraction methods in the field of artificial intelligence.
Frequently Updated Research
Stay updated on advancements in neural network training methods, point cloud data processing techniques, and applications in artificial intelligence.
Questions about Point Cloud Data Processing
How does this method improve the efficiency of processing point cloud data?
This method efficiently extracts features from point cloud data using neural networks, improving processing speed and accuracy.
What are the potential real-world applications of this technology?
This technology has applications in autonomous vehicles, robotics, augmented reality, and environmental monitoring, among others.
Original Abstract Submitted
A point cloud data processing method, a neural network training method, and a related device are provided. The method may be applied to the field of point cloud data processing in the field of artificial intelligence. The method may include: obtaining point cloud data corresponding to a target environment, where the point cloud data is divided into a plurality of target cubes; generating an initial feature of each target cube based on initial information of a target point in each target cube; updating initial features of the plurality of target cubes based on an attention mechanism to obtain updated features of the plurality of target cubes; and performing a feature processing operation on the updated features of the plurality of target cubes to obtain a prediction result corresponding to the point cloud data.
