ABSTRACT: Anomaly detection in complex crowd scenes is a challenging task due to the inherent variability in crowd behaviors, interactions, and scales. This paper proposes a novel hybrid model that ...

Specifically, we propose a Variational Lane Detection Network (VLD-Net) using a Conditional Variational Auto-Encoder (CVAE) as the generative network to produce multiple lane maps as candidates, ...

Variational Autoencoders (VAEs) are an artificial neural network architecture to generate new data. They are similar to regular autoencoders, which consist of an encoder and decoder. The encoder ...

As 5G adoption gains momentum, the problem will get far worse, requiring more sophisticated DDoS detection/mitigation mechanisms," according to Anand Dutta, Head of Cyber Security Solutions and ...

What does a VAE do? In short, it improves the generated images. A VAE is trained for certain aspects of the image, and the default VAE bundled in our UI (vae-ft-mse-840000-ema-pruned) improves the ...

Next, the demo trains a VAE model using the 389 images. The demo concludes by using ... The discovery of this idea in the original 2013 research paper ("Auto-Encoding Variational Bayes" by D.P. Kingma ...