Results 51 to 60 of about 20,368 (248)
Non-uniform Blur Kernel Estimation via Adaptive Basis Decomposition
, 2021 Motion blur estimation remains an important task for scene analysis and image restoration. In recent years, the removal of motion blur in photographs has seen impressive progress in the hands of deep learning-based methods, trained to map directly from blurry to sharp images.
Carbajal, Guillermo +4 more
openaire +2 more sources
TacScope: A Miniaturized Vision‐Based Tactile Sensor for Surgical Applications
Advanced Robotics Research, EarlyView.TacScope is a compact, vision‐based tactile sensor designed for robot‐assisted surgery. By leveraging a curved elastomer surface with pressure‐sensitive particle redistribution, it captures high‐resolution 3D tactile feedback. TacScope enables accurate tumor detection and shape classification beneath soft tissue phantoms, offering a scalable, low‐cost ...
Md Rakibul Islam Prince +3 more
wiley +1 more source
Blind Deconvolution for Image Deblurring Based on Edge Enhancement and Noise Suppression
IEEE Access, 2018 This paper denotes to obtain an accuracy blur kernel and a shape image. An efficient method that blind deconvolution for image deblurring based on edge enhancement and noise suppression is proposed. First, we exploited an edge detection method to extract
Chengtao Cai, Haiyang Meng, Qidan Zhu
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
Continual Learning for Multimodal Data Fusion of a Soft Gripper
Advanced Robotics Research, EarlyView.Models trained on a single data modality often struggle to generalize when exposed to a different modality. This work introduces a continual learning algorithm capable of incrementally learning different data modalities by leveraging both class‐incremental and domain‐incremental learning scenarios in an artificial environment where labeled data is ...
Nilay Kushawaha, Egidio Falotico
wiley +1 more source
Iterative multi‐scale residual network for deblurring
IET Image Processing, 2021 In dynamic scene deblurring, recent neural network–based methods have been very successful. But with the improvement of deep deblurring performance, network structure and learning become more complicated.
Tianlin Zhang, Jinjiang Li, Zhen Hua
doaj +1 more source
Learning to Deblur Images with Exemplars
, 2018 Human faces are one interesting object class with numerous applications. While significant progress has been made in the generic deblurring problem, existing methods are less effective for blurry face images.
Hu, Zhe +3 more
core +1 more source
Advanced Science, EarlyView.vEMRec is a frequency‐adaptive computational framework for three‐dimensional alignment in volume electron microscopy. It integrates feature‐based rigid alignment with Gaussian filter‐guided elastic registration to correct rigid misalignments and nonlinear distortions while preserving structural fidelity.
Zhenbang Zhang +7 more
wiley +1 more source
A Motion Deblur Method Based on Multi-Scale High Frequency Residual Image Learning
IEEE Access, 2020 Non-uniform blind deblurring of dynamic scenes has always been a challenging problem in image processing because of the diverse of blurring sources. Traditional methods based on energy minimization cannot make accurate kernel estimation. It leads to that
Keng-Hao Liu +3 more
doaj +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