Flux AI: Anomaly detection

Anomaly detection Flux Artworks

Flowchart diagram showing user chat records leading to data cleaning steps including desensitization. Automated labeling and manual re-labeling processes converge to create a high-quality corpus. This corpus is used for model training before going through a testing phase. User feedback generates an anomaly detection process. Violations lead to tracing analysis while normal content returns to chat records. A strategy to avoid account bans involving IP rotation and behavior simulation is presented after detection.
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Comprehensive flowchart illustrating the data processing workflow for AI model training and anomaly detection

data processing
AI Model Training
Machine Learning