Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group

Lost in Translation: The Critical Role of Attention in Adaptive Image Reconstruction

Not Accessible

Your library or personal account may give you access

Abstract

We propose a novel attention-based deep learning framework for reconstructing images from compressively sensed measurements. Our method leverages knowledge of the sampling basis and structured sampling patterns, highlighting the importance of learning adaptive features from measurements.

© 2023 The Author(s)

PDF Article
More Like This
Recent Advances in Sparse and Ultra-Sparse Reconstruction for Medical Imaging

Wen-Chih Liu, Jayanth Pratap, Abhiram R. Bhashyam, Neal C. Chen, Quanzheng Li, and Xiang Li
HTh2C.1 Digital Holography and Three-Dimensional Imaging (DH) 2023

CMSnet: State of the Art Deep Learning Multiscale Reconstruction for Compressive Sensing

Vladislav Kravets and Adrian Stern
JW5C.3 3D Image Acquisition and Display: Technology, Perception and Applications (3D) 2022

End-to-End Optimized Adversarial Deep Compressed Super-Resolution Imaging via Pattern Scanning

Kangning Zhang, Junze Zhu, and Weijian Yang
CM2E.6 Computational Optical Sensing and Imaging (COSI) 2021

Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All rights reserved, including rights for text and data mining and training of artificial technologies or similar technologies.