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Local feature descriptors have been widely used in fine-grained visual object search thanks to their robustness in scale and rotation variation and cluttered background. However, the performance of such descriptors drops under severe…

计算机视觉与模式识别 · 计算机科学 2019-01-03 Zhenwei Miao , Kim-Hui Yap , Xudong Jiang , Subbhuraam Sinduja , Zhenhua Wang

In this paper, we deal with time-invariant spatially coupled low-density parity-check convolutional codes (SC-LDPC-CCs). Classic design approaches usually start from quasi-cyclic low-density parity-check (QC-LDPC) block codes and exploit…

Low-density parity check (LDPC) codes are a well known class of Pauli stabiliser Hamiltonians that furnish fixed-point realisations of nontrivial gapped phases such as symmetry breaking and topologically ordered (including fracton) phases.…

强关联电子 · 物理学 2025-12-05 Pranay Gorantla , Tzu-Chen Huang

This paper proposes to extend local image features in 3D to include invariance to discrete symmetry including inversion of spatial axes and image contrast. A binary feature sign $s \in \{-1,+1\}$ is defined as the sign of the Laplacian…

计算机视觉与模式识别 · 计算机科学 2022-06-01 Laurent Chauvin , William Wells , Matthew Toews

Unlike standard object classification, where the image to be classified contains one or multiple instances of the same object, indoor scene classification is quite different since the image consists of multiple distinct objects. Further,…

计算机视觉与模式识别 · 计算机科学 2016-11-03 Munawar Hayat , Salman H. Khan , Mohammed Bennamoun , Senjian An

In this paper, we study a new class of high-rate spatially coupled LDPC (SC-LDPC) codes based on the convolutional self-orthogonal codes (CSOCs) first introduced by Massey. The SC-LDPC codes are constructed by treating the irregular graph…

信息论 · 计算机科学 2025-02-18 Daniel J. Costello, , Min Zhu , David G. M. Mitchell , Michael Lentmaier

In this paper we describe a new formulation for the 3D salient local features based on the voxel grid inspired by the Scale Invariant Feature Transform (SIFT). We use it to identify the salient keypoints (invariant points) on a 3D voxelized…

计算机视觉与模式识别 · 计算机科学 2011-05-16 Afzal Godil , Asim Imdad Wagan

In this paper, we propose a new texture descriptor, completed local derivative pattern (CLDP). In contrast to completed local binary pattern (CLBP), which involves only local differences at each scale, CLDP encodes the directional variation…

图像与视频处理 · 电气工程与系统科学 2018-12-12 Yuting Hu , Zhiling Long , Ghassan AlRegib

Discrete time crystals (DTCs) are nonequilibrium phases of matter characterized by robust subharmonic order parameter dynamics. We report a new type of DTC in a periodically driven surface code, the subharmonic signature of which is only…

量子物理 · 物理学 2021-08-04 Raditya Weda Bomantara

Visual Saliency is the capability of vision system to select distinctive parts of scene and reduce the amount of visual data that need to be processed. The presentpaper introduces (1) a novel approach to detect salient regions by…

计算机视觉与模式识别 · 计算机科学 2016-07-12 Sikha O K , Sachin Kumar S , K P Soman

We study samples of natural images for which a set of statistical characteristics is computed and scale-invariant properties of samples are demonstrated computationally. Computations of the power spectrum are carried out and a power-law…

计算机视觉与模式识别 · 计算机科学 2022-04-28 Maxim Koroteev , Kirill Aistov

Spatially-coupled (SC) LDPC codes have recently emerged as an excellent choice for error correction in modern data storage and communication systems due to their outstanding performance. It has long been known that irregular graph codes…

信息论 · 计算机科学 2019-06-17 Homa Esfahanizadeh , Ruiyi Wu , Lara Dolecek

Discontinuous Shear Thickening (DST) fluids exhibit unique instability properties in a wide range of flow conditions. We present numerical simulations of a scalar model for DST fluids in a planar simple shear using the Smoothed Particle…

流体动力学 · 物理学 2024-08-16 Peter Angerman , Bjornar Sandnes , Ryohei Seto , Marco Ellero

Convolutional Neural Network (CNN) features have been successfully employed in recent works as an image descriptor for various vision tasks. But the inability of the deep CNN features to exhibit invariance to geometric transformations and…

计算机视觉与模式识别 · 计算机科学 2015-04-27 Konda Reddy Mopuri , R. Venkatesh Babu

Circular-harmonic spectra are a compact representation of local image features in two dimensions. It is well known that the computational complexity of such transforms is greatly reduced when polar separability is exploited in steerable…

计算机视觉与模式识别 · 计算机科学 2020-11-09 Hugh L Kennedy

Topological invariants are global properties of the ground-state wave function, typically defined as winding numbers in reciprocal space. Over the years, a number of topological markers in real space have been introduced, allowing to map…

介观与纳米尺度物理 · 物理学 2024-01-17 Nicolas Baù , Antimo Marrazzo

Most popular hand-crafted key-point detectors such as Harris corner, SIFT, SURF aim to detect corners, blobs, junctions or other human defined structures in images. Though being robust with some geometric transformations, unintended…

计算机视觉与模式识别 · 计算机科学 2020-10-14 Thanh Hong-Phuoc , Ling Guan

We exploit a key result from visual psychophysics---that individuals perceive shape qualitatively---to develop the use of a geometrical/topological "invariant'' (the Morse--Smale complex) relating image structure with surface structure.…

计算机视觉与模式识别 · 计算机科学 2018-07-30 Benjamin S. Kunsberg , Steven W. Zucker

We study spatial coherence properties of a system composed of periodic silver nanoparticle arrays covered with a fluorescent organic molecule (DiD) film. The evolution of spatial coherence of this composite structure from the weak to the…

光学 · 物理学 2014-04-17 L. Shi , T. K. Hakala , H. T. Rekola , J. -P. Martikainen , R. J. Moerland , P. Törmä

We consider spatially coupled low-density parity-check codes with finite smoothing parameters. A finite smoothing parameter is important for designing practical codes that are decoded using low-complexity windowed decoders. By optimizing…

信息论 · 计算机科学 2019-07-09 Laurent Schmalen , Vahid Aref
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