Radar chart sequences of daily courier behavior, classified by a CNN and bidirectional LSTM, are reported to outperform static radar-image and tabular baselines on a private churn dataset.
Physical review letters89(1), 015002 (2002) 16 S
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CV 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
RadarSeq: A Temporal Vision Framework for User Churn Prediction via Radar Chart Sequences
Radar chart sequences of daily courier behavior, classified by a CNN and bidirectional LSTM, are reported to outperform static radar-image and tabular baselines on a private churn dataset.