18289100. NEURAL NETWORKS WITH ADAPTIVE STANDARDIZATION AND RESCALING simplified abstract (GOOGLE LLC)
Contents
NEURAL NETWORKS WITH ADAPTIVE STANDARDIZATION AND RESCALING
Organization Name
Inventor(s)
NEURAL NETWORKS WITH ADAPTIVE STANDARDIZATION AND RESCALING - A simplified explanation of the abstract
This abstract first appeared for US patent application 18289100 titled 'NEURAL NETWORKS WITH ADAPTIVE STANDARDIZATION AND RESCALING
Simplified Explanation:
This patent application describes methods, systems, and apparatus for processing a network input using a neural network with a normalization block. The neural network includes layers that standardize data to generate adaptive standardization values, which are then used to standardize the input data for further processing.
- The patent application focuses on processing network inputs using a neural network with a normalization block.
- The neural network includes layers that standardize data to generate adaptive standardization values.
- These adaptive standardization values are used to standardize the input data for further processing.
- The normalization block plays a crucial role in ensuring the data is processed efficiently and accurately.
- The technology aims to improve the performance and accuracy of neural networks in processing network inputs.
Potential Applications:
The technology described in this patent application has potential applications in various fields, including:
- Image and speech recognition systems
- Natural language processing applications
- Autonomous vehicles
- Healthcare diagnostics
- Financial forecasting models
Problems Solved:
This technology addresses the following specific problems:
- Improving the efficiency and accuracy of neural networks in processing network inputs
- Enhancing the performance of machine learning models
- Standardizing data to ensure consistent processing results
Benefits:
The benefits of this technology include:
- Improved accuracy in processing network inputs
- Enhanced performance of neural networks
- Consistent and reliable data standardization
- Increased efficiency in data processing tasks
Commercial Applications:
Title: Enhanced Neural Network Processing for Improved Data Standardization
This technology has significant commercial potential in industries such as:
- Technology and software development companies
- Data analytics and machine learning firms
- Healthcare and medical imaging companies
- Financial services and investment firms
- Automotive and transportation industries
Questions about Enhanced Neural Network Processing for Improved Data Standardization:
1. How does the normalization block in the neural network improve data processing efficiency? 2. What are the key advantages of using adaptive standardization values in standardizing input data?
Original Abstract Submitted
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for processing a network input using a neural network to generate a network output. The neural network includes a normalization block that is between a first neural network layer and a second neural network layer in the neural network. Processing the network input using the neural network comprises: receiving a first layer output from the first neural network layer; processing data derived from the first layer output using standardization neural network layers of the normalization block to generate one or more adaptive standardization values; standardizing the first layer output using the adaptive standardization values to generate a standardized first layer output; generating a normalization block output from the standardized first layer output; and providing the normalization block output as an input to the second neural network layer.
