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We explore the Potts model on the generalized decorated square lattice, with both nearest (J1) and next-neighbor (J2) interactions. Using the tensor renormalization-group method augmented by higher-order singular value decompositions, we…

Statistical Mechanics · Physics 2024-06-26 M. P. Qin , J. Chen , Q. N. Chen , Z. Y. Xie , X. Kong , H. H. Zhao , B. Normand , T. Xiang

The increased demand for online prediction and the growing availability of large data sets drives the need for computationally efficient models. While exact Gaussian process regression shows various favorable theoretical properties…

Machine Learning · Computer Science 2021-08-02 Armin Lederer , Alejandro Jose Ordonez Conejo , Korbinian Maier , Wenxin Xiao , Jonas Umlauft , Sandra Hirche

The goal of this paper is to present a new efficient image segmentation method based on evolutionary computation which is a model inspired from human behavior. Based on this model, a four layer process for image segmentation is proposed…

Computer Vision and Pattern Recognition · Computer Science 2017-12-07 Roohollah Aslanzadeh , Kazem Qazanfari , Mohammad Rahmati

We present a new solution of the asymmetric two-matrix model in the large $N$ limit which only involves a saddle point analysis. The model can be interpreted as Ising in the presence of a magnetic field, on random dynamical lattices with…

Statistical Mechanics · Physics 2007-05-23 P. Zinn-Justin

Interactive image segmentation is a topic of many studies in image processing. In a conventional approach, a user marks some pixels of the object(s) of interest and background, and an algorithm propagates these labels to the rest of the…

Computer Vision and Pattern Recognition · Computer Science 2019-01-10 Fabricio Aparecido Breve

For problems in image processing and many other fields, a large class of effective neural networks has encoder-decoder-based architectures. Although these networks have made impressive performances, mathematical explanations of their…

Computer Vision and Pattern Recognition · Computer Science 2023-09-18 Xue-Cheng Tai , Hao Liu , Raymond Chan

Deep learning methods driven by the low-rank regularization have achieved attractive performance in dynamic magnetic resonance (MR) imaging. However, most of these methods represent low-rank prior by hand-crafted nuclear norm, which cannot…

Image and Video Processing · Electrical Eng. & Systems 2022-08-11 Chentao Cao , Zhuo-Xu Cui , Qingyong Zhu , Congcong Liu , Dong Liang , Yanjie Zhu

The Ising model was generalized to a system of cells interacting exclusively by presence of shared spins. Within the cells there are interactions of any complexity, the simplest intracell interactions come down to the Ising model. The…

Statistical Mechanics · Physics 2021-02-23 Vadym Sakhno , Mykola Sakhno

The problem of image segmentation is known to become particularly challenging in the case of partial occlusion of the object(s) of interest, background clutter, and the presence of strong noise. To overcome this problem, the present paper…

Computer Vision and Pattern Recognition · Computer Science 2010-06-15 Robert Sheng Xu , Oleg Michailovich , Magdy Salama

Instance segmentation of remote sensing images (RSIs) is an essential task for a wide range of applications such as land planning and intelligent transport. Instance segmentation of RSIs is constantly plagued by the unbalanced ratio of…

Computer Vision and Pattern Recognition · Computer Science 2024-09-12 Xuexue Li

Image models are central to all image processing tasks. The great advancements in digital image processing would not have been made possible without powerful models which, themselves, have evolved over time. In the past decade, patch-based…

Image and Video Processing · Electrical Eng. & Systems 2019-12-10 Davood Karimi

Critical aspects of computational imaging systems, such as experimental design and image priors, can be optimized through deep networks formed by the unrolled iterations of classical model-based reconstructions (termed physics-based…

Computer Vision and Pattern Recognition · Computer Science 2020-03-13 Michael Kellman , Kevin Zhang , Jon Tamir , Emrah Bostan , Michael Lustig , Laura Waller

With applications ranging from metabolomics to histopathology, quantitative phase microscopy (QPM) is a powerful label-free imaging modality. Despite significant advances in fast multiplexed imaging sensors and deep-learning-based inverse…

The Cellular Potts Model (CPM) is a lattice based modeling technique which is widely used for simulating cellular patterns such as foams or biological tissues. Despite its realism and generality, the standard Monte Carlo algorithm used in…

Soft Condensed Matter · Physics 2016-09-14 Marc Durand , Etienne Guesnet

Time evolution and scattering simulation in phenomenological models are of great interest for testing and validating the potential for near-term quantum computers to simulate quantum field theories. Here, we simulate one-particle…

Quantum Physics · Physics 2021-05-26 Kübra Yeter-Aydeniz , George Siopsis , Raphael C. Pooser

There is no an exact solution to three-dimensional (3D) finite-size Ising model (referred to as the Ising model hereafter for simplicity) and even two-dimensional (2D) Ising model with non-zero external field to our knowledge. Here by using…

General Physics · Physics 2018-10-12 Rong Qiang Wei

An arbitrary quantum-optical process (channel) can be completely characterized by probing it with coherent states using the recently developed coherent-state quantum process tomography (QPT) [Lobino et al., Science 322, 563 (2008)]. In…

Quantum Physics · Physics 2013-08-09 Xiang-Bin Wang , Zong-Wen Yu , Jia-Zhong Hu , Adam Miranowicz , Franco Nori

We propose an importance sampling scheme to estimate the partition function of the two-dimensional ferromagnetic Ising model and the two-dimensional ferromagnetic $q$-state Potts model, both in the presence of an external magnetic field.…

Computation · Statistics 2015-02-06 Mehdi Molkaraie

We note that it is possible to construct a bond vertex model that displays q-state Potts criticality on an ensemble of phi3 random graphs of arbitrary topology, which we denote as ``thin'' random graphs in contrast to the fat graphs of the…

Statistical Mechanics · Physics 2009-10-31 D. Johnston

In a seminal paper, Weitz showed that for two-state spin systems, such as the Ising and hardcore models from statistical physics, correlation decay on trees implies correlation decay on arbitrary graphs. The key gadget in Weitz's reduction…

Data Structures and Algorithms · Computer Science 2025-02-11 Kuikui Liu , Nitya Mani , Francisco Pernice