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What is Neural Networks for Anomaly Detection Review about?

This paper reviews neural network approaches for anomaly detection. It examines the most relevant neural network outlier detection algorithms, compares their benefits and drawbacks, and evaluates their performance on benchmark datasets. The review identifies autoencoder neural networks, convolutional neural networks, recurrent neural networks, and generative adversarial networks as promising for outlier detection.

Author

congduy0908

Language

EN