Dynamic Image Moderation System with Customizable Thresholds
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Solution Overview
Problem
Current image moderation systems are not dynamic enough to quickly and effectively adjust to different environments and characteristics such as age and culture.
Innovation Solution
An image moderation management system that uses computer vision models and customizable thresholds to identify and moderate images based on various categories, allowing for dynamic adjustment of moderation rules based on environment and characteristics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If current image moderation systems use fixed moderation rules, then the system structure is simple, but the system cannot dynamically adjust to different environments and characteristics
Solution Approach 1:
The patent implements dynamic moderation rules that can be adjusted based on different environments and characteristics. The system allows administrators to customize moderation thresholds and parameters for different contexts (e.g., different age groups, cultural settings, platforms), enabling the system to adapt its behavior dynamically rather than using fixed rules.
Solution Approach 2:
The system changes moderation parameters such as sensitivity thresholds, detection thresholds, and classification criteria based on the specific environment and characteristics being moderated. This allows the same system to adapt to different contexts by adjusting parameters rather than requiring completely different systems.
2Adaptability or versatility
If the system uses customizable thresholds and rules, then the adaptability to different environments improves, but the complexity of configuring and managing the system increases
Solution Approach 1:
The system segments the moderation configuration into distinct, manageable components such as separate threshold settings, category definitions, and environment parameters. This segmentation allows users to configure only the relevant parameters for their specific needs without being overwhelmed by the entire system complexity.
Solution Approach 2:
The system incorporates feedback mechanisms that allow administrators to review moderation results and adjust thresholds based on actual performance data. This iterative process simplifies configuration by learning from past results and automatically optimizing parameters, reducing the manual configuration burden.
Data Source
AI summary
Methods, non-transitory computer readable media, and image moderation management computing apparatuses that receive a request that includes an image to be moderated. A percentage match of the received image against one or more computer vision models for one or more different categories is identified. A determination is made when the percentage match is within a range between customizable lower and upper thresholds for one or more of the different categories. Image moderation analysis data on the received image from one of one or more moderator computing devices is obtained when the percentage match is within the range. One or more stored rules on the received image are executed based on the obtained image moderation analysis data.


