18615655. METHOD FOR TRAINING NEURAL NETWORK MODEL AND APPARATUS simplified abstract (Huawei Technologies Co., Ltd.)
Contents
- 1 METHOD FOR TRAINING NEURAL NETWORK MODEL AND APPARATUS
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 METHOD FOR TRAINING NEURAL NETWORK MODEL AND APPARATUS - 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 Neural Network Model Training
- 1.13 Original Abstract Submitted
METHOD FOR TRAINING NEURAL NETWORK MODEL AND APPARATUS
Organization Name
Inventor(s)
METHOD FOR TRAINING NEURAL NETWORK MODEL AND APPARATUS - A simplified explanation of the abstract
This abstract first appeared for US patent application 18615655 titled 'METHOD FOR TRAINING NEURAL NETWORK MODEL AND APPARATUS
Simplified Explanation
This patent application describes methods and apparatuses for training neural network models, specifically focusing on improving the precision of a lower-precision model by using data from a higher-precision model.
Key Features and Innovation
- Obtaining annotation data of a service to be processed by two neural network models with varying precision levels.
- Training a second neural network model using the annotation data to improve its precision.
- Updating a first neural network model based on the trained second neural network model to enhance its performance.
Potential Applications
This technology can be applied in various fields such as image recognition, natural language processing, and predictive analytics where neural network models are used.
Problems Solved
This technology addresses the issue of improving the precision of neural network models, especially when dealing with models of varying precision levels.
Benefits
- Enhanced performance of neural network models.
- Improved accuracy in processing services.
- Better utilization of data for training neural networks.
Commercial Applications
- Image recognition software for security systems.
- Chatbot development for customer service.
- Predictive analytics tools for financial forecasting.
Prior Art
Readers can explore prior research on neural network model training techniques, precision improvement methods, and data annotation strategies.
Frequently Updated Research
Stay informed about the latest advancements in neural network training methodologies, precision enhancement techniques, and data annotation practices.
Questions about Neural Network Model Training
How does this technology improve the performance of neural network models?
This technology enhances performance by training a lower-precision model using data from a higher-precision model.
What are the potential applications of this innovation beyond neural network training?
The potential applications include image recognition, natural language processing, and predictive analytics in various industries.
Original Abstract Submitted
This disclosure provides methods and apparatuses for training a neural network model. One example method performed by a terminal device includes: obtaining annotation data of a service, wherein the service is to be processed by a first neural network model and a second neural network model, and wherein precision of the first neural network model is lower than precision of the second neural network model, training a second neural network model by using the annotation data of the service to obtain a trained second neural network model, and updating a first neural network model based on the trained second neural network model.
