From a reconstruction perspective, the blocks in the pre-event scene are rebuilt from denoised versions of post-event blocks by means of convolutional denoising autoencoders. In order to perform this ...

The purpose of this project is to develop a comprehensive deep learning-based system that performs both image reconstruction and tumor detection for medical MRI scans. Initially, the system is ...

Hence, this research proposes an Autoencoder-based Temporal Convolutional Network (AE-TCN) for real-time anomaly detection in large-scale network traffic data. This process begins with the collection ...

Owing to the immense popularity of ray-tracing and path tracing rendering algorithms for visual effects, there has been a surge of interest in developing filtering and reconstruction methods to deal ...