IEEE

Selective Imitation Enhanced Deep Reinforcement Learning for AAV Navigation and Obstacle Avoidance With Sparse Rewards

Abstract: Deep reinforcement learning (DRL) has emerged as a promising solution for autonomous operations of autonomous aerial vehicles (AAVs) in unknown environments. However, learning to navigate ...
IEEE

ADDomics: Enhancing Multiomics Fusion with Autoencoders and Deep Neural Networks

Abstract: Advancing precision medicine and understanding biological systems and enhancing disease categorization have benefited greatly from multi-omics integration. Nevertheless, current strategies ...
GitHub

Diffusion-Scheduled Denoising Autoencoders for Anomaly Detection (AnoDDAE)

This repository provides reproducible implementation of the anomaly detection method based on a denoising autoencoder architecture with diffusion noise scheduling mechanism inspired by diffusion ...
Scientific Research Publishing

Rai, S., Bhatt, J.S. and Patra, S.K. (2021) An Unsupervised Deep Learning Framework for Medical Image Denoising.

ABSTRACT: Magnetic Resonance Imaging (MRI) is commonly applied to clinical diagnostics owing to its high soft-tissue contrast and lack of invasiveness. However, its sensitivity to noise, attributable ...
Scientific Research Publishing

Kumar, R.R. and Priyadarshi, R. (2024) Denoising and Segmentation in Medical Image Analysis: A Comprehensive Review on Machine Learning and Deep Learning Approaches. Multimedia ...

ABSTRACT: Magnetic Resonance Imaging (MRI) is commonly applied to clinical diagnostics owing to its high soft-tissue contrast and lack of invasiveness. However, its sensitivity to noise, attributable ...