Results 11 to 20 of about 1,202 (247)
A Plug-and-Play Deep Image Prior [PDF]
ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021 Deep image priors (DIP) offer a novel approach for the regularization that leverages the inductive bias of a deep convolutional architecture in inverse problems. However, the quality of DIP approaches often degrades when the number of iterations exceeds a certain threshold due to overfitting.
Zhaodong Sun +3 more
core +3 more sources
Recovery Analysis for Plug-and-Play Priors using the Restricted Eigenvalue Condition [PDF]
CoRR, 2021 The plug-and-play priors (PnP) and regularization by denoising (RED) methods have become widely used for solving inverse problems by leveraging pre-trained deep denoisers as image priors. While the empirical imaging performance and the theoretical convergence properties of these algorithms have been widely investigated, their recovery properties have ...
Liu, Jiaming +3 more
core +6 more sources
Deep plug-and-play priors for spectral snapshot compressive imaging
Photonics Research, 2021 We propose a plug-and-play (PnP) method that uses deep-learning-based denoisers as regularization priors for spectral snapshot compressive imaging (SCI). Our method is efficient in terms of reconstruction quality and speed trade-off, and flexible enough to be ready to use for different compressive coding mechanisms.
Siming Zheng +7 more
openaire +2 more sources
Tuning-Free Plug-and-Play Hyperspectral Image Deconvolution With Deep Priors [PDF]
IEEE Transactions on Geoscience and Remote Sensing, 2023 IEEE Trans. Geosci. Remote sens., to be published. Manuscript submitted Jun. 30, 2022; revised Oct. 25, 2022, and Dec. 06, 2022; and accepted Feb.
Wang, Xiuheng +2 more
openaire +5 more sources
Dimensionality reduced plug and play priors for improving photoacoustic tomographic imaging with limited noisy data. [PDF]
Biomed Opt Express, 2021 The reconstruction methods for solving the ill-posed inverse problem of photoacoustic tomography with limited noisy data are iterative in nature to provide accurate solutions.
Awasthi N +3 more
europepmc +2 more sources
IEEE AccessAccurate classification of small targets in high-resolution medical images remains challenging because salient signals are diluted by extensive background and existing methods have structural limitations.
Shukai Ding +3 more
doaj +2 more sources
Plug-and-Play Image Restoration With Deep Denoiser Prior [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022 An extended version of IRCNN (CVPR17).
Zhang, Kai +5 more
openaire +5 more sources
2022 IEEE International Conference on Image Processing (ICIP), 2022 The past few years have seen a surge of activity around integration of deep learning networks and optimization algorithms for solving inverse problems. Recent work on plug-and-play priors (PnP), regularization by denoising (RED), and deep unfolding has shown the state-of-the-art performance of such integration in a variety of applications. However, the
Abdullah H. Al-Shabili +3 more
openaire +3 more sources
Diffusion Models as Plug-And-Play Priors
Advances in Neural Information Processing Systems 35, 2022 NeurIPS 2022; code: https://github.com/AlexGraikos ...
Alexandros Graikos +3 more
openaire +4 more sources
Deep plug-and-play prior for hyperspectral image restoration
Neurocomputing, 2022 code at https://github.com/Zeqiang-Lai ...
Zeqiang Lai, Kaixuan Wei, Ying Fu 0001
openaire +2 more sources