Samsung electronics co., ltd. (20240242072). APPARATUS AND METHOD WITH OUT-OF-DISTRIBUTION DATA DETECTION simplified abstract
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APPARATUS AND METHOD WITH OUT-OF-DISTRIBUTION DATA DETECTION
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Inventor(s)
APPARATUS AND METHOD WITH OUT-OF-DISTRIBUTION DATA DETECTION - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240242072 titled 'APPARATUS AND METHOD WITH OUT-OF-DISTRIBUTION DATA DETECTION
Simplified Explanation: The patent application describes an apparatus and method for detecting out-of-distribution data using a neural network model.
- **Key Features and Innovation:**
- Utilizes one or more processors to execute instructions for data detection. - Determines maximum loss value based on output data and neighboring data. - Detects if input data is out-of-distribution using a threshold.
- **Potential Applications:**
- Enhancing data security by detecting anomalies in datasets. - Improving the accuracy of machine learning models by filtering out-of-distribution data.
- **Problems Solved:**
- Addressing the challenge of identifying out-of-distribution data in neural network models. - Enhancing the reliability and performance of machine learning algorithms.
- **Benefits:**
- Increased data accuracy and reliability. - Enhanced security measures for data processing. - Improved efficiency in machine learning applications.
- **Commercial Applications:**
- This technology can be applied in various industries such as finance, healthcare, and cybersecurity to improve data analysis and anomaly detection processes.
- **Prior Art:**
- Researchers can explore prior studies on anomaly detection in machine learning models to understand the evolution of this technology.
- **Frequently Updated Research:**
- Stay updated on advancements in anomaly detection techniques in neural networks to enhance the efficiency of out-of-distribution data detection.
Questions about out-of-distribution data detection:
1. *How does the apparatus determine the maximum loss value for detecting out-of-distribution data?*
- The apparatus calculates loss values for neighboring data within a reference distance from the input data and identifies the maximum loss value to determine if the input data is out-of-distribution.
2. *What are the potential implications of using this technology in cybersecurity applications?*
- This technology can significantly enhance cybersecurity measures by accurately detecting anomalies in datasets, thereby improving threat detection and data protection.
Original Abstract Submitted
an apparatus and method with out-of-distribution data detection is provided. the apparatus includes one or more processors configured to execute instructions; and one or more memories storing the instructions, wherein, the execution of the instructions by the one or more processors configures the one or more processors to generate output data using a neural network model provided input data; determine, based on the output data, a maximum loss value among calculated loss values that correspond to neighboring data within a reference distance from the input data; and detect, based on the maximum loss value and a threshold, whether the input data is out-of-distribution (ood) data that is different from in-distribution data corresponding to training data used in a training of the neural network model.
