annotated bibliography for below articles In apa no specific word count

  

References

Jiang, C., Song, J., Liu, G., Zheng, L., & Luan, W. (2018). Credit card fraud detection: A novel approach using aggregation strategy and feedback mechanism. IEEE Internet of Things Journal, 5(5), 3637-3647.

Li, Z., Liu, G., & Jiang, C. (2020). Deep representation learning with full center loss for credit card fraud detection. IEEE Transactions on Computational Social Systems, 7(2), 569-579.

Tingfei, H., Guangquan, C., & Kuihua, H. (2020). Using Variational Auto Encoding in Credit Card Fraud Detection. IEEE Access, 8, 149841-149853.

Zheng, L., Liu, G., Yan, C., & Jiang, C. (2018). Transaction fraud detection based on total order relation and behavior diversity. IEEE Transactions on Computational Social Systems, 5(3), 796-806.

Zhang, Z., Chen, L., Liu, Q., & Wang, P. (2020). A Fraud Detection Method for Low-Frequency Transaction. IEEE Access, 8, 25210-25220.

Zanetti, M., Jamhour, E., Pellenz, M., Penna, M., Zambenedetti, V., & Chueiri, I. (2017). A tunable fraud detection system for advanced metering infrastructure using short-lived patterns. IEEE Transactions on Smart grid, 10(1), 830-840.

Huang, D., Mu, D., Yang, L., & Cai, X. (2018). CoDetect: Financial fraud detection with anomaly feature detection. IEEE Access, 6, 19161-19174.

Omair, B., & Alturki, A. (2020). A Systematic Literature Review of Fraud Detection Metrics in Business Processes. IEEE Access, 8, 26893-26903.

Zhu, Bing & Yang, Wenchuan & Wang, Huaxuan & Yuan, Yuan. (2018). A hybrid deep learning model for consumer credit scoring. 205-208. 10.1109/ICAIBD.2018.8396195.

Nie, G., Wei, R., Zhang, L., Tian, Y., and Shi, Y., 2011. Credit card churn forecasting by logistic regression and decision tree. Expert Systems with Applications 38, 12, 15273-15285. 

Cecotti, Hubert & Rivera, Agustin & Farhadloo, Majid & Villarreal, Miguel. (2020). Grape detection with Convolutional Neural Networks. Expert Systems with Applications. 159. 113588. 10.1016/j.eswa.2020.113588.

Yifei, R. A. O. (2016). Big Data Algorithm Applied to Credit Risk Assessment Model. International Journal of Simulation–Systems, Science & Technology, 17(42).

Sarigul, Mehmet & Ozyildirim, B.M. & Avci, Mutlu. (2019). Differential convolutional neural network. Neural Networks. 116. 10.1016/j.neunet.2019.04.025.

Zhou, F.-Y & Jin, Linpeng & Dong, Jianfang. (2017). Review of Convolutional Neural Network. Jisuanji Xuebao/Chinese Journal of Computers. 40. 1229-1251. 10.11897/SP.J.1016.2017.01229. 

Dawood, E. A. E., Elfakhrany, E., & Maghraby, F. A. (2019). Improve Profiling Bank Customer’s Behavior Using Machine Learning. IEEE Access, 7, 109320-109327.

Kvamme, Håvard & Sellereite, Nikolai & Aas, Kjersti & Sjursen, Steffen. (2018). Predicting Mortgage Default using Convolutional Neural Networks. Expert Systems with Applications. 102. 10.1016/j.eswa.2018.02.029.

Zhou, X., Zhang, W., & Jiang, Y. (2020). Personal Credit Default Prediction Model Based on Convolution Neural Network. Mathematical Problems in Engineering, 2020.

Yu, Z. Y., & Zhao, S. F. (2011, December). Bank credit risk management early warning and decision-making based on BP neural networks. In 2011 IEEE International Symposium on IT in Medicine and Education (Vol. 2, pp. 528-532). IEEE.

Cheng, D., Xiang, S., Shang, C., Zhang, Y., Yang, F., & Zhang, L. (2020, April). Spatio-Temporal Attention-Based Neural Network for Credit Card Fraud Detection. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 34, No. 01, pp. 362-369).