cellular automata-based anomaly detection in pattern recognition
Cellular automata-based anomaly detection in pattern recognition is a method that uses mathematical models, specifically cellular automata, to identify rare or unusual patterns within a larger dataset. It involves analyzing the behavior and interactions of individual elements in the dataset to detect and classify anomalies or irregularities that deviate from expected patterns.
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