DeepAnT [36], a convolutional autoencoder that forecasts future time points and flags deviations as anomalies, has been effectively used for IoT monitoring across multiple deployments. Kara et al. [46 ...

In this paper, the stacked convolutional autoencoder network structure constructed with fusion selection kernel attention mechanism is based on FCAE, which consists of an encoder and a decoder.

This projects detect Anomalous Behavior through live CCTV camera feed to alert the police or local authority for faster response time. We are using Spatio Temporal AutoEncoder and more importantly ...

In this work, a convolutional neural network autoencoder has been used to reconstruct fingerprint images. An autoencoder is a technique, which is able to replicate data in the images. The advantage of ...

The network architecture is exhibits in Figure 2. The key technical contribution of our method is a convolutional autoencoder-based boundary and mask adversarial learning framework, which uses both ...

Convolutional autoencoder, domain adaptation, and shallow classifiers. We first separately applies NMF on MIMIC and CHOA data for feature dimensionality reduction, then used two separate CAE models to ...