aceLeveraging transfer learning with deep learning for crime prediction
Crime remains a crucial concern regarding ensuring a safe and secure environment for the public. Numerous efforts have been made to predict crime, emphasizing the importance of employing deep learning approaches for precise predictions. However, sufficient crime data and resources for training state-of-the-art deep learning-based crime prediction systems pose a challenge. To address this issue, this study adopts the transfer learning paradigm. Moreover, this study fine-tunes state-of-the-art statistical and deep…
Fine-tuned BiLSTM with transfer learning achieved lower prediction error and faster execution for weekly and monthly crime trends, evaluated on Chicago, New York and Lahore datasets, to support law enforcement prevention and control.
Evidence
- Peer-reviewedPLOS ONE2024-04-17
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Truvace Impact Record TRV-2026-0453, v1: “Leveraging transfer learning with deep learning for crime prediction.” Truvace, 2026-07-20. /record/TRV-2026-0453 (accessed at citation time). sha256 b1c622b202ee1371…
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