State-of-the-art approaches for image deconvolution problems, including modern deep learning architectures
M Makarkin, D Bratashov - Micromachines, 2021 - mdpi.com
In modern digital microscopy, deconvolution methods are widely used to eliminate a number
of image defects and increase resolution. In this review, we have divided these methods into …
of image defects and increase resolution. In this review, we have divided these methods into …
A Unified Framework for Microscopy Defocus Deblur with Multi-Pyramid Transformer and Contrastive Learning
Defocus blur is a persistent problem in microscope imaging that poses harm to pathology
interpretation and medical intervention in cell microscopy and microscope surgery. To …
interpretation and medical intervention in cell microscopy and microscope surgery. To …
Line Laser Measurement Error Compensation Under Vibration Conditions With Improved DeblurGAN
Q Bo, Z Miao, H Liu, X Liu… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
In the process of line laser measurement, the vibration of the sensor or the workpiece will
cause the light stripe image to be blurred, resulting in unstable extraction of the laser light …
cause the light stripe image to be blurred, resulting in unstable extraction of the laser light …
Deep structured layers for instance-level optimization in 2D and 3D vision
F Kokkinos - 2023 - discovery.ucl.ac.uk
The approach we present in this thesis is that of integrating optimization problems as layers
in deep neural networks. Optimization-based modeling provides an additional set of tools …
in deep neural networks. Optimization-based modeling provides an additional set of tools …
Sub-millisecond Video Synchronization of Multiple Android Smartphones
This paper addresses the problem of building an affordable easy-to-setup synchronized
multi-view camera system, which is in demand for many Computer Vision and Robotics …
multi-view camera system, which is in demand for many Computer Vision and Robotics …