23 papers · ranked by Valyu relevance
Hongyan Zhou, Liang Yao
—The current learning process of deep learning, regardless of any deep neural network (DNN) architecture and/or learning algorithm used, is essentially a single resolution training. We explore multiresolution learning and show that multiresolution learning can significantly improve robustness of DNN models for both 1D…
Shaolong Chen, Changzhen Qiu, Weiping Yang, Zhiyong Zhang + 1 more
'Alessandro Bevilacqua'] The latest medical image segmentation methods uses UNet and transformer structures with great success. Multiscale feature fusion is one of the important factors affecting the accuracy of medical image segmentation. Existing transformer-based UNet methods do not comprehensively explore…
Lamiaa Abdel-Hamid
Chest computer tomography (CT) provides a readily available and efficient tool for COVID-19 diagnosis. Wavelet and contourlet transforms have the advantages of being localized in both space and time. In addition, multiresolution analysis allows for the separation of relevant image information in the different subbands.…
Shaolong Chen, Changzhen Qiu, Weiping Yang, Zhiyong Zhang
The automatic segmentation of cardiac magnetic resonance (MR) images is the basis for the diagnosis of cardiac-related diseases. However, the segmentation of cardiac MR images is a challenging task due to the inhomogeneity of MR images intensity distribution and the unclear boundaries between adjacent tissues. In this…
Heikkilä, Tommi
MultiResolution Low-Rank decomposition is formulated for regularization of dynamic image sequences. The decomposition applies a local low-rank decomposition on a sequence of discrete wavelet transforms. Its effective formulation as a regularization functional is discussed and numerically tested for dynamic X-ray…
Peter Wind, Magnar Bjørgve, Anders Brakestad, Gabriel A. Gerez S. + 3 more
Analysis Code for Molecular Electronic Structure Calculations: Performance and Scaling Properties Authors: ['Peter Wind' 'Magnar Bjørgve' 'Anders Brakestad' 'Gabriel A. Gerez S.' 'Stig Rune Jensen' 'Roberto Di Remigio Eikås' 'Luca Frediani'] MRChem is a code for molecular electronic structure calculations, based on a…
Wonguk Cho, Daekyung Lee, Beom Jun Kim
International trade networks are complex systems that consist of overlapping multiple trade blocs of varying sizes. However, the resulting structures of community detection in trade networks often fail to accurately represent the complexity of international trade. To address this issue, we propose a multiresolution…
Vojtěch Bartoň, Ivana Ihnatova, Jiří Kalina, Garry Paul Codling + 3 more
Accurate peak detection is a critical first step in high-resolution mass spectrometry (HRMS) data analysis. Most existing tools rely on centroiding and grid-based assumptions, which simplify the raw profile data at the cost of information loss and reduced detection accuracy. We present MRH, a novel peak detection…
Lili Wang, Xuehuai Shi, Yi Liu
Recently, virtual reality (VR) technology has been widely used in medical, military, manufacturing, entertainment, and other fields. These applications must simulate different complex material surfaces, various dynamic objects, and complex physical phenomena, increasing the complexity of VR scenes. Current computing…
Esley Torres García, Raúl Pinto Cámara, Alejandro Linares, Damián Martínez + 22 more
Mean-Shift Super Resolution (MSSR) is a principle based on the Mean Shift theory that improves the spatial resolution in fluorescence images beyond the diffraction limit. MSSR works on low- and high-density fluorophore images, is not limited by the architecture of the detector (EM-CCD, sCMOS, or photomultiplier-based…
Jian Li, Siwang Zhou
Image rescaling (IR) seeks to determine the optimal lowresolution (LR) representation of a high-resolution (HR) image to reconstruct a high-quality super-resolution (SR) image. Typically, HR images with resolutions exceeding 2K possess rich information that is unevenly distributed across the image. Traditional image…
Authors not listed
This conceptual paper introduces the Adaptive Multi-Resolution Modeling Framework (AMRMF), a novel technique designed to revolutionize chemical engineering by integrating multi-scale simulations, quantum-inspired algorithms, advanced uncertainty quantification, and Bayesian inference. The framework bridges theoretical…
Luca Savant Aira, Diego Valsesia, Andrea Bordone Molini, Giulia Fracastoro + 2 more
Flow Authors: ['Luca Savant Aira' 'Diego Valsesia' 'Andrea Bordone Molini' 'Giulia Fracastoro' 'Enrico Magli' 'Andrea Mirabile'] Abstract—Multi-image super-resolution (MISR) allows to increase the spatial resolution of a low-resolution (LR) acquisition by combining multiple images carrying complementary information in…
Ritam Dutta, Bheem Dutt Joshi, Vineet Kumar, Amira Sharief + 4 more
Despite advancements in remote sensing, satellite imagery is underutilized in conservation research. Multispectral data from various sensors have great potential for mapping landscapes, but distinct spectral and spatial resolution capabilities are crucial for accurately classifying wildlife habitats. Our study aimed to…
Jing Sun, Qiangqiang Yuan, Huanfeng Shen, Jie Li + 2 more
The objective of image super-resolution is to reconstruct a high-resolution (HR) image with the prior knowledge from one or several low-resolution (LR) images. However, in the real world, due to the limited complementary information, the performance of both single-frame and multi-frame super-resolution reconstruction…
Zhengzhong Tu, Peyman Milanfar, Hossein Talebi
Image resizing operation is a fundamental preprocessing module in modern computer vision. Throughout the deep learning revolution, researchers have overlooked the potential of alternative resizing methods beyond the commonly used resizers that are readily available, such as nearestneighbors, bilinear, and bicubic. The…
Yonatan Kleerekoper, Mohammad Kurtam, Yonatan Keselman, Shai Abramson + 4 more
Functional connectivity (FC) is fundamentally non-stationary, undergoing continuous reconfigurations that track shifting behavioral and cognitive states. Despite the importance of these transitions, existing analytical frameworks struggle to reconcile the high-dimensional nature of these reconfigurations with the need…
Efe Ozturk, Abhijeet Venkataraman, Felix G. Rivera Moctezuma, Ahmet F. Coskun
Mass spectrometry imaging (MSI) is a powerful technique for spatially resolved analysis of metabolites and other biomolecules within biological tissues. However, the inherent low spatial resolution of MSI often limits its ability to provide detailed cellular-level information. To address this limitation, we propose a…
Authors not listed
Hyperstructures and their hierarchical extensions—SuperHyperStructures—provide a versatile algebraic language for modeling multi-level and interdependent systems [1,2]. In materials and chemical sciences, structural descriptions naturally span a broad spectrum of characteristic length scales, commonly organized as…
Hong Cao, Abhishek Saha, Lisa V. Poulikakos
In fluid flow imaging, intensity gradients are a good measure of spatial variations in scalar properties, which play an important role in controlling transport processes. However, current flow imaging techniques exhibit system-limited spatial resolutions, thus inhibiting the ability to accurately detect intensity…
Bo Wang, Xin Liao, Yong Ni, Li Zhang + 9 more
'Yongmao Liu' 'Xianyue Sun' 'Yikuan Ou' 'Qinning Wu' 'Lei Shi' 'Zhixiong Yang' 'Lin Lan'] Objective Cerebral aneurysms are classified as severe cerebrovascular diseases due to hidden and critical onset, which seriously threaten life and health. An effective strategy to control intracranial aneurysms is the regular…
Chengyi Xie, Jianing Wang, Xin Diao, Xiaoxiao Wang + 1 more
Desorption electrospray ionization mass spectrometry imaging (DESI MSI) is a valuable tool for label-free, spatially resolved molecular analysis of biological tissues. However, its spatial resolution has been limited to tens of micrometers due to constraints in spray geometry and solvent flow, hindering single-cell…
Authors not listed
Scanning emission-based microscopies, such as X-ray fluorescence (XRF) and energy-dispersive X-ray spectroscopy, offer nanometer-scale chemical maps, but suffer from long acquisition times and radiation damage. Lower-flux and shorter dwell time scans mitigate this problem, but the resulting signal loss can only…