Results 51 to 60 of about 9,413,043 (217)
ESFFA: Early‐Stage Feature Frequency Attack in Cross‐Domain Few‐Shot Learning
IET Computer Vision, Volume 20, Issue 1, January/December 2026.This paper addresses the challenge of cross‐domain few‐shot learning (CD‐FSL), where models often rely on frequency shortcuts rather than semantic features. We propose ESFFA (Early‐Stage Feature Frequency Attack), a novel method that perturbs low‐frequency statistics and masks high‐frequency components in shallow feature maps to reduce shortcut ...
Xu Wang +4 more
wiley +1 more source
Computation, 2021 The aim of the present paper is to improve an existing blind image deblurring algorithm, based on an independent component learning paradigm, by manifold calculus.
Simone Fiori
doaj +1 more source
Learning a Discriminative Prior for Blind Image Deblurring [PDF]
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018 This paper is accepted by CVPR2018 as ...
Lerenhan Li +5 more
openaire +3 more sources
IET Computer Vision, Volume 20, Issue 1, January/December 2026.This survey systematically reviews state‐of‐the‐art license plate recognition methods, with a focus on hybrid CNN‐transformer frameworks and the joint optimisation of detection and recognition for real‐world deployment. It further analyses existing datasets, highlights persistent challenges, such as domain generalisation, and outlines pathways towards ...
SanXing Deng +3 more
wiley +1 more source
Motion Deblurring from a Single Image [PDF]
, 2018 With the information explosion, a tremendous amount photos is captured and shared via social media everyday. Technically, a photo requires a finite exposure to accumulate light from the scene. Thus, objects moving during the exposure generate motion blur
Jin, Meiguang
core
IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingBlind deblurring of optical remote sensing images has been a longstanding challenge. In recent years, many learning-based deblurring algorithms have been greatly developed.
Zhiyuan Li +4 more
doaj +1 more source
Blind UAV Images Deblurring Based on Discriminative Networks
Sensors, 2018 Unmanned aerial vehicles (UAVs) have become an important technology for acquiring high-resolution remote sensing images. Because most space optical imaging systems of UAVs work in environments affected by vibrations, the optical axis motion and image ...
Ruihua Wang +4 more
doaj +1 more source
Sensors, 2020 Image deblurring has been a challenging ill-posed problem in computer vision. Gaussian blur is a common model for image and signal degradation. The deep learning-based deblurring methods have attracted much attention due to their advantages over the ...
Quan Zhou, Mingyue Ding, Xuming Zhang
doaj +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
PARAMETRIC BLIND IMAGE DEBLURRING WITH GRADIENT BASED SPECTRAL KURTOSIS MAXIMIZATION [PDF]
, 2018 Blind image deconvolution/deblurring (BID) is a challenging task due to lack of prior information about the blurring process and image. Noise and ringing artefacts resulted during the restoration process further deter fine restoration of the pristine ...
Hujun Yin, Aftab Khan
core +1 more source