Results 21 to 30 of about 9,181,016 (294)
3D Computational Ghost Imaging [PDF]
The Rochester Conferences on Coherence and Quantum Optics and the Quantum Information and Measurement meeting, 2013 Computational ghost imaging retrieves the spatial information of a scene using a single pixel detector. By projecting a series of known random patterns and measuring the back reflected intensity for each one, it is possible to reconstruct a 2D image of ...
Bowman, Ardrian +6 more
core +2 more sources
Computational imaging with low-order OAM beams at microwave frequencies [PDF]
Sci Rep, 2020 With the distinguished wavefront characteristics of vortex electromagnetic wave carrying orbital angular momentum (OAM), the OAM beams have been exploited for radar imaging in recent years.
Kang Liu +3 more
semanticscholar +2 more sources
A Two-step-training Deep Learning Framework for Real-time Computational Imaging without Physics Priors [PDF]
Opt Express, 2020 Deep learning (DL) is a powerful tool in computational imaging for many applications. A common strategy is to use a preprocessor to reconstruct a preliminary image as the input to a neural network to achieve an optimized image.
Ruibo Shang +2 more
semanticscholar +2 more sources
Plug-and-Play Methods for Integrating Physical and Learned Models in Computational Imaging: Theory, algorithms, and applications [PDF]
IEEE Signal Processing Magazine, 2022 Plug-and-play (PnP) priors constitute one of the most widely used frameworks for solving computational imaging problems through the integration of physical models and learned models. PnP leverages high-fidelity physical sensor models and powerful machine
U. Kamilov +3 more
semanticscholar +1 more source
Near Field Computational Imaging with RIS Generated Virtual Masks [PDF]
IEEE Wireless Communications and Networking Conference, 2023 Near field computational imaging has been recognized as a promising technique for non-destructive and highly accurate detection of the target. Meanwhile, reconfigurable intelligent surface (RIS) can flexibly control the scattered electro-magnetic (EM ...
Yuhua Jiang +4 more
semanticscholar +1 more source
Just-in-time deep learning for real-time X-ray computed tomography
Scientific Reports, 2023 Real-time X-ray tomography pipelines, such as implemented by RECAST3D, compute and visualize tomographic reconstructions in milliseconds, and enable the observation of dynamic experiments in synchrotron beamlines and laboratory scanners.
Adriaan Graas +3 more
doaj +1 more source
Deep Optical Coding Design in Computational Imaging: A data-driven framework [PDF]
IEEE Signal Processing Magazine, 2022 Computational optical imaging (COI) systems leverage optical coding elements (CEs) in their setups to encode a high-dimensional scene in a single or in multiple snapshots and decode it by using computational algorithms.
H. Arguello +12 more
semanticscholar +1 more source
Beam filtration for object-tailored X-ray CT of multi-material cultural heritage objects
Heritage Science, 2023 Computed tomography (CT) is a powerful non-invasive tool to analyze cultural heritage objects by allowing museum professionals to obtain 3D information about the objects’ interior.
Maximilian B. Kiss +6 more
doaj +1 more source
Scientific Data, 2023 Recent research in computational imaging largely focuses on developing machine learning (ML) techniques for image reconstruction, which requires large-scale training datasets consisting of measurement data and ground-truth images.
Maximilian B. Kiss +4 more
doaj +1 more source
CT-based data generation for foreign object detection on a single X-ray projection
Scientific Reports, 2023 Although X-ray imaging is used routinely in industry for high-throughput product quality control, its capability to detect internal defects has strong limitations.
Vladyslav Andriiashen +3 more
doaj +1 more source