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This paper adopts the Generative Adversarial Network to obtain data distribution through unsupervised learning and generate more information.
Abstract—Deep learning is used in various application, and there are many outstanding performances in many fields recently. Generative Adversarial Networks�...
In this paper, a trajectory anomaly detection method for aircraft in terminal airspace surrounding an airport is proposed. This method, as an effective and�...
Jan 20, 2023 � The present study adopted a GAN variant with autoencoders to create a hybrid model for detecting anomalies and hazards in the airport environment.
Jan 18, 2023 � Anomaly detection is an important research topic in the field of artificial intelligence and visual scene understanding.
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The most significant challenge in real-world anomaly detection problems is the high imbalance of available data (i.e., non-anomalous versus anomalous data).
Missing: Transportation | Show results with:Transportation
We propose and demonstrate the use of a GAN architecture, known as the fast Anomaly Generative Adversarial Network ( -AnoGAN), to solve the problem of anomaly�...
Missing: Airport | Show results with:Airport
Sep 27, 2023 � In this paper, generative adversarial network (GAN)-based anomaly detection and forecasting are studied for 5G vertical applications.
Feb 15, 2024 � Abstract. Due to the scarcity of abnormal condition data in industrial applications, one-class classification models.
Oct 22, 2021 � Anomaly detection has become an indispensable tool for modern society, applied in a wide range of applications, from detecting fraudulent�...