MECHANISMS FOR IDENTIFYING FINANCIAL RISKS AND IMPLEMENTING EFFECTIVE REMOTE CONTROL
Keywords:
budget funds, risk analysis, information systems, artificial intelligence technologies, big data.Abstract
This article proposes an effective information systems architecture for identifying and managing financial risks in remote monitoring of budget spending.
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J. Redmon, S. Divvala, R. Girshick, A. Farhadi, “You Only Look Once: Unified, Real-Time Object Detection”, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 779-788, 2016.
URL: https://doi.org/10.1109/CVPR.2016.91
A. Radford et al., “Learning Transferable Visual Models from Natural Language Supervision”, arXiv preprint arXiv:2103.00020, 2021.
URL: https://arxiv.org/abs/2103.00020
T. Mikolov, K. Chen, G. Corrado, J. Dean, “Efficient Estimation of Word Representations in Vector Space”, arXiv preprint arXiv:1301.3781, 2013.
URL: https://arxiv.org/abs/1301.3781
J. Devlin, M.-W. Chang, K. Lee, K. Toutanova, “BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding”, arXiv preprint arXiv:1810.04805, 2018.URL: https://arxiv.org/abs/1810.04805
I. Sutskever, O. Vinyals, Q. V. Le, “Sequence to Sequence Learning with Neural Networks”, Advances in Neural Information Processing Systems (NIPS), vol. 27, 2014. URL: https://arxiv.org/abs/1409.3215
V. Vapnik, The Nature of Statistical Learning Theory, Springer, 1995.
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