56 citations · 113 across the 12 of their papers we have counts for
7 papers · 1 filter
Recovery Analysis for Plug-and-Play Priors using the Restricted Eigenvalue Condition
Jiaming Liu, M. Salman Asif, Brendt Wohlberg +1
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…
Diagram Image Retrieval using Sketch-Based Deep Learning and Transfer Learning
Manish Bhattarai, Diane Oyen, Juan Castorena +2
Resolution of the complex problem of image retrieval for diagram images has yet to be reached. Deep learning methods continue to excel in the fields of object detection and image c…
TGGLines: A Robust Topological Graph Guided Line Segment Detector for Low Quality Binary Images
Ming Gong, Liping Yang, Catherine Potts +3
Line segment detection is an essential task in computer vision and image analysis, as it is the critical foundation for advanced tasks such as shape modeling and road lane line det…
Regularized Fourier Ptychography using an Online Plug-and-Play Algorithm
Yu Sun, Shiqi Xu, Yunzhe Li +3
The plug-and-play priors (PnP) framework has been recently shown to achieve state-of-the-art results in regularized image reconstruction by leveraging a sophisticated denoiser with…
An Online Plug-and-Play Algorithm for Regularized Image Reconstruction
Yu Sun, Brendt Wohlberg, Ulugbek S. Kamilov
Plug-and-play priors (PnP) is a powerful framework for regularizing imaging inverse problems by using advanced denoisers within an iterative algorithm. Recent experimental evidence…
Convolutional Sparse Coding with Overlapping Group Norms
Brendt Wohlberg
The most widely used form of convolutional sparse coding uses an regularization term. While this approach has been successful in a variety of applications, a limitation of…