The TransUAAE-CapGen architecture consists of a hybrid UNet-based Advereasrial Autoencoder (AAE) for feature extraction and a transformer for caption generation. The hybrid UNet-based AAE extracted ...

Accurate estimation of two-dimensional (2D) multi-obstacle steady-state flows is crucial in various scientific and engineering disciplines, yet conventional methods often fall short in precision and ...

This project proposes a wavelet-enhanced UNet architecture for image segmentation tasks, specifically targeting improvements in boundary precision and contour clarity. By incorporating wavelet ...

The autoencoder network model for HIV classification, proposed in this paper, thus outperforms the conventional feedforward neural network models and is a much better classifier. Current Science is a ...