Deep Compressed Sensing

Deep compressed sensing (DCS) leverages deep learning to improve compressed sensing techniques, aiming to reconstruct high-quality signals from significantly undersampled measurements. Current research focuses on developing efficient and robust deep neural network architectures, including recurrent and convolutional networks, often incorporating self-supervised learning to reduce reliance on labeled data and improve generalization. These advancements are impacting various fields, such as medical imaging (e.g., MRI) and IoT sensor networks, by enabling faster, more efficient data acquisition and processing with improved reconstruction quality.