Results 51 to 60 of about 16,544 (207)
A Fractional-Order Fidelity-Based Total Generalized Variation Model for Image Deblurring
Fractal and Fractional, 2023 Image deblurring is a fundamental image processing task, and research for efficient image deblurring methods is still a great challenge. Most of the currently existing methods are focused on TV-based models and regularization term construction; little ...
Juanjuan Gao +3 more
doaj +1 more source
Convolutional Deblurring for Natural Imaging
, 2019 In this paper, we propose a novel design of image deblurring in the form of one-shot convolution filtering that can directly convolve with naturally blurred images for restoration.
Hosseini, Mahdi S. +1 more
core +1 more source
Artificial Intelligence Revolution in Transcriptomics: From Single Cells to Spatial Atlases
Advanced Science, Volume 13, Issue 5, 27 January 2026.Single‐cell RNA sequencing and spatial transcriptomics have unveiled cellular heterogeneity and tissue organization with unprecedented resolution. Artificial intelligence (AI) now plays a pivotal role in interpreting these complex data. This review systematically surveys AI applications across the entire analytic workflow and offers practical guidance ...
Shixin Li +7 more
wiley +1 more source
Fast and easy blind deblurring using an inverse filter and PROBE
, 2017 PROBE (Progressive Removal of Blur Residual) is a recursive framework for blind deblurring. Using the elementary modified inverse filter at its core, PROBE's experimental performance meets or exceeds the state of the art, both visually and quantitatively.
J Kotera +11 more
core +1 more source
Magnetic Resonance in Medicine, Volume 95, Issue 1, Page 400-410, January 2026.Abstract Purpose To analytically define a spiral waveform and trajectory that match the constraints of gradient frequency, slew rate, and amplitude. Theory and Methods Piecewise analytical solutions for gradient waveforms under the desired constraints are derived using the circle of an involute rather than an Archimedean spiral.
Guruprasad Krishnamoorthy, James G. Pipe
wiley +1 more source
DeblurGAN: Blind Motion Deblurring Using Conditional Adversarial Networks
, 2018 We present DeblurGAN, an end-to-end learned method for motion deblurring. The learning is based on a conditional GAN and the content loss . DeblurGAN achieves state-of-the art performance both in the structural similarity measure and visual appearance ...
Budzan, Volodymyr +4 more
core +1 more source
Enhancing convolutional neural network generalizability via low‐rank weight approximation
IET Image Processing, Volume 20, Issue 1, January/December 2026.A self‐supervised framework is proposed for image denoising based on the Tucker low‐rank tensor approximation. With the proposed design, we are able to characterize our denoiser with fewer parameters and train it based on a single image, which considerably improves the model's generalizability and reduces the cost of data acquisition. Abstract Noise is
Chenyin Gao, Shu Yang, Anru R. Zhang
wiley +1 more source
IET Image Processing, Volume 20, Issue 1, January/December 2026.This paper proposes a low‐light image enhancement and denoising algorithm tailored for tunnel scenes based on computer vision and deep learning technologies. On this basis, a tunnel pedestrian detection method based on connected domain dynamic threshold segmentation is designed, which can reduce the computational resources for identifying pedestrian ...
Yudan Tian +4 more
wiley +1 more source
Reblur2Deblur: Deblurring Videos via Self-Supervised Learning
, 2018 Motion blur is a fundamental problem in computer vision as it impacts image quality and hinders inference. Traditional deblurring algorithms leverage the physics of the image formation model and use hand-crafted priors: they usually produce results that ...
Chen, Huaijin +5 more
core +1 more source
Deblurring by Realistic Blurring
, 2020 Existing deep learning methods for image deblurring typically train models using pairs of sharp images and their blurred counterparts. However, synthetically blurring images do not necessarily model the genuine blurring process in real-world scenarios ...
Li, Hongdong +6 more
core +1 more source