Results 121 to 130 of about 2,159,265 (282)

Applied aspects of modern non-blind image deconvolution methods

Компьютерная оптика
The focus of this paper is the study of modern non-blind image deconvolution methods and their application to practical tasks. The aim of the study is to determine the current state-of-the-art in non-blind image deconvolution and to identify the ...
O.B. Chaganova, A.S. Grigoryev, D.P. Nikolaev, I.P. Nikolaev   +3 more
doaj   +1 more source

A Bayesian approach to parameter estimation for kernel density estimation via transformations [PDF]

In this paper, we present a Markov chain Monte Carlo (MCMC) simulation algorithm for estimating parameters in the kernel density estimation of bivariate insurance claim data via transformations.
David Pitt, Xueyuan Wu, Qing Liu, Xibin Zhang   +3 more
core  

Self-paced kernel estimation for robust blind image deblurring

, 2017
The challenge in blind image deblurring is to remove the effects of blur with limited prior information about the nature of the blur process. Existing methods often assume that the blur image is produced by linear convolution with additive Gaussian noise.
Tan, M., Gong, D., Yanning Zhang, Qinfeng Shi, Hengel, A., Dong Gong, Mingkui Tan, Anton van den Hengel, Shi, Q., Zhang, Y.   +9 more
core   +1 more source

Formation Control With Obstacle Avoidance of Underwater Swarms Based on Relative Visual Feedback

Journal of Field Robotics, EarlyView.
ABSTRACT Underwater multi‐robot and swarm systems require advanced methodologies for controlling collective behavior. Conventional single‐robot techniques, such as tethering, sonar imaging, and acoustic localization, are not scalable or effective for swarm applications.
Andrea Infanti, Saverio Iacoponi, Saif Alameri, Mohamed El Hanbaly, Mohammed Tarnini, Cesare Stefanini, Giulia De Masi, Federico Renda   +7 more
wiley   +1 more source

Integrating Image Segmentation and Deep Learning to Improve Radio Frequency Propagation Models

International Journal of Satellite Communications and Networking, EarlyView.
ABSTRACT This paper proposes a multi‐sensor approach to improve radio frequency (RF) propagation models, which play a key role in the rapidly expanding field of connected vehicle technology. Focusing on the 1‐ to 20‐GHz frequency range, which is critical for both satellite‐to‐vehicle and base station‐to‐vehicle communications, our study introduces a ...
Jonathan Israel, Xavier Boulanger, Vegard Arneson   +2 more
wiley   +1 more source

Blind Image Deblurring via Bayesian Estimation Using Expected Loss

IEEE Access
This paper introduces a new approach to single image blind deblurring via Bayesian estimation using expected loss, diverging from traditional maximum a posteriori (MAP) estimation methods that are limited by the delta kernel problem-a phenomenon where ...
Jinook Lee, Moon Gi Kang
doaj   +1 more source

FEWT: Frequency‐Enhanced Wavelet‐Based Transformer for Multimodal Wheeled Bimanual Manipulation

SmartBot, EarlyView.
An embodied mobile bimanual robot learns dexterous manipulation skills through imitation learning with multimodal perception. The integration of vision, proprioception, and tactile sensing establishes a comprehensive perception–action loop, enabling the robot to continuously understand, interact with, and adapt to complex physical environments.
Jiaxin Huang, Hanyu Liu, Yunsheng Ma, Jian Shen, Yilin Zheng, Jiayi Wen, Zhigong Song   +6 more
wiley   +1 more source

Dual-Branch CNN–Mamba Method for Image Defocus Deblurring

Applied Sciences
Defocus deblurring is a challenging task in the fields of computer vision and image processing. The irregularity of defocus blur kernels, coupled with the limitations of computational resources, poses significant difficulties for defocused image ...
Wenqi Zhao, Chunlei Wu, Jing Lu, Ran Li
doaj   +1 more source

Simultaneous Tumor Segmentation, Image Restoration, and Blur Kernel Estimation in PET Using Multiple Regularizations. [PDF]

Comput Vis Image Underst, 2017
Li L, Wang J, Lu W, Tan S.
europepmc   +1 more source

Imaging Ionic Displacements Across Inclined Ferroelectric Domains by a Reciprocity Approach to 4D‐STEM

Small, EarlyView.
Four‐dimensional STEM comprises a vast portfolio of electron microscopy methods in one data set, conventional plane‐wave illumination TEM being one of them. Here, the principle of reciprocity is employed to produce true structural projections of misoriented ferroelectric domains at atomic resolution. By reciprocal TEM imaging from four‐dimensional STEM
Jean Felix Dushimineza, Max Leo Leidl, Sebastian Sturm, Thibaud Denneulin, Knut Müller‐Caspary   +4 more
wiley   +1 more source