Results 51 to 60 of about 1,364,847 (158)
Accelerated MR Elastography Using Learned Neural Network Representation
Magnetic Resonance in Medicine, EarlyView.ABSTRACT Purpose To develop a deep‐learning method for achieving fast high‐resolution MR elastography from highly undersampled data without the need for high‐quality training datasets. Methods We first reframed the deep neural network representation as a nonlinear extension of the linear subspace model, then used it to represent and reconstruct MRE ...
Xi Peng
wiley +1 more source
A user‐friendly platform for deep‐learning‐based image enhancement in scanning X‐ray microscopy
Journal of Synchrotron Radiation, EarlyView.A graphical user interface is developed for deep‐learning‐based image enhancement in scanning X‐ray microscopy. By incorporating the intensity of the probe and scan parameters, the graphical user interface enables accessible and reproducible super‐resolution and deblurring of scanning X‐ray datasets, supporting improved analysis of X‐ray fluorescence ...
Xiaoyin Zheng +7 more
wiley +1 more source
Thermal Image Reconstruction Using Deep Learning
IEEE Access, 2020 A high-resolution thermal camera is very expensive and is thus difficult to be used. Furthermore, thermal images become blurred in various cases of object motion, camera shaking, and camera defocusing. To solve these problems, a previous super-resolution
Ganbayar Batchuluun +4 more
doaj +1 more source
Computer Graphics Forum, EarlyView.Abstract Correlation‐based rendering techniques continue to advance, and efficiently exploiting correlations between pixel estimates has become increasingly important. The deep combiner framework [BHHM20] allows us to fuse independent and correlated pixel estimates but focuses solely on spatial correlations.
W. Zhou, E. Hughes, T. Hachisuka
wiley +1 more source
FMD-cGAN: Fast Motion Deblurring using Conditional Generative Adversarial Networks
, 2021 In this paper, we present a Fast Motion Deblurring-Conditional Generative Adversarial Network (FMD-cGAN) that helps in blind motion deblurring of a single image. FMD-cGAN delivers impressive structural similarity and visual appearance after deblurring an
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Holistic 3D Body Reconstruction From a Blurred Single Image
IEEE Access, 2022 Holistic human pose and shape reconstruction receive huge interest since it restores detailed human pose and shape including facial expression and finger-level hand shape.
Joshua Santoso, Williem, In Kyu Park
doaj +1 more source
International Endodontic Journal, EarlyView.ABSTRACT Background Computer vision methods based on artificial intelligence (AI) have found numerous applications in endodontic diagnosis and treatment planning. While most current applications employ discriminative deep learning models for detection and classification tasks, the field is now witnessing the rise of generative AI (GenAI), a class of AI
Hossein Mohammad‐Rahimi +6 more
wiley +1 more source
StripWinformer: Locally-Enhanced Transformer for Image Motion Deblurring
IEEE AccessSingle image motion deblurring is a critical low-level computer vision task, aiming to restore clear and sharp images from motion-corrupted counterparts.
Tsung-Han Tsai, Yz-Heng Lin
doaj +1 more source
Temperature reconstruction of infrared images with motion deblurring [PDF]
Journal of Sensors and Sensor Systems, 2018 Infrared images of an uncooled microbolometer camera can show significant blurring effects while recording a moving object. The electrical signal in the pixel of a microbolometer detector decays exponentially; hence, the moving object is mapped to ...
B. Oswald-Tranta
doaj +1 more source
Blur-Robust Object Detection Using Feature-Level Deblurring via Self-Guided Knowledge Distillation
IEEE Access, 2022 Images captured from real-world environments often include blur artifacts resulting from camera movement, dynamic object motion, or out-of-focus.
Sung-Jin Cho +3 more
doaj +1 more source