A proposed CRNIM hybrid CNN-GRU model is claimed to reach 97.1% accuracy and 0.94 AUROC on the Elliptic Bitcoin dataset for anomaly detection.
Transformers in Opinion Mining: Addressing Semantic Complexity and Model Challenges in NLP,
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Deep Learning for Cross-Border Transaction Anomaly Detection in Anti-Money Laundering Systems
A proposed CRNIM hybrid CNN-GRU model is claimed to reach 97.1% accuracy and 0.94 AUROC on the Elliptic Bitcoin dataset for anomaly detection.