AutoencoderClass imbalanceDeep learningThe rapid growth of network-related services in the last decade has produced a huge amount of sensitive data on the internet. But networks are very much prone to intrusions where unauthorized users attempt to access sensitive information and even disrupt the ...
The idea of using a deep autoencoder to encode seismic waveform features and then use them in different seismological applications is appealing. In this paper, we designed tests to evaluate this idea of using autoencoders as feature extractors for different seismological applications, such as event...
1) For simplicity, thanks to the strong feature representation ability of vision transformers, the ViTPose pipeline can be extremely simple. For example, it does not require any specific domain knowledge to design the backbone encoder and enjoys a plain and non-hierarchical encoder structure by ...
It applies to univariate time series and uses various techniques such as wavelet transform and deep learning autoencoders. 3. Application of Generic Patterns for an SOA IDS Unlike firewalls, for example, IDSs are reactive measures in that they detect potential attacks only when they occur, which...