Target detection algorithm failure cause analysis method, device and equipment

By analyzing the causes of failure in target detection algorithms through causal reasoning and iterative calculation, the problem of algorithm failure in practical applications was solved, and qualitative and quantitative analysis was achieved, improving the accuracy and efficiency of the analysis.

CN117541912BActive Publication Date: 2026-06-26INST OF SOFTWARE - CHINESE ACAD OF SCI
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Patent Information

Application Number
CN202311368393.7
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2023-10-20
Publication Date
2026-06-26
Estimated Expiration
2043-10-20

AI Technical Summary

Technical Problem

Existing object detection algorithms often fail in practical applications, failing to accurately locate and classify objects in images or videos, leading to potential security risks. Furthermore, the reasons for failure are complex and difficult to explain.

Method used

By training and testing target detection algorithms with datasets, failure data is collected. Causal reasoning and iterative calculation methods are used to analyze the causal relationship between algorithm failure and potential failure influencing factors, calculate the weight values ​​of failure influencing factors, and achieve qualitative and quantitative failure cause analysis.

Benefits of technology

It improves the accuracy and efficiency of target detection algorithm failure cause analysis, and can automatically reverse-engineer the main failure causes, thereby improving the reliability of the algorithm.

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Abstract

The present disclosure relates to a failure cause analysis method, device and equipment of a target detection algorithm, and belongs to the technical field of target detection. The method comprises: training and / or testing the target detection algorithm through a data set, and obtaining failure data of the target detection algorithm in the training and / or testing process, each piece of failure data comprising a failure type and measurement values of a plurality of failure influence factors; performing causal reasoning on the failure process of the target detection algorithm based on the failure data to obtain failure causal relationships of the target detection algorithm under at least one failure type, the failure causal relationships comprising causal relationships between the plurality of failure influence factors; and iteratively calculating failure weight values of the plurality of failure influence factors based on the failure causal relationships corresponding to each failure type in the at least one failure type. The present disclosure can qualitatively and quantitatively analyze the failure causes of the target detection algorithm.
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