English
Related papers

Related papers: ROAST: Rapid Orthogonal Approximate Slepian Transf…

200 papers

Rotation moment invariants have been of great interest in image processing and pattern recognition. This paper presents a novel kind of rotation moment invariants based on the Slepian functions, which were originally introduced in the…

Computer Vision and Pattern Recognition · Computer Science 2016-07-06 Cuiming Zou , Kit Ian Kou

Parallel imaging is ubiquitous in MRI, enabling diverse applications such as ultra-high-resolution functional and quantitative imaging with greater temporal resolution or reduced scan times respectively. Successful unfolding is contingent…

We consider the frequency domain form of proper orthogonal decomposition (POD) called spectral proper orthogonal decomposition (SPOD). Spectral POD is derived from a space-time POD problem for statistically stationary flows and leads to…

Fluid Dynamics · Physics 2018-06-05 Aaron Towne , Oliver T. Schmidt , Tim Colonius

This paper provides an a~priori error analysis of a localized orthogonal decomposition method (LOD) for the numerical stochastic homogenization of a model random diffusion problem. If the uniformly elliptic and bounded random coefficient…

Numerical Analysis · Mathematics 2020-12-03 Julian Fischer , Dietmar Gallistl , Daniel Peterseim

Accurate 6D object pose estimation is fundamental to robotic manipulation and grasping. Previous methods follow a local optimization approach which minimizes the distance between closest point pairs to handle the rotation ambiguity of…

Computer Vision and Pattern Recognition · Computer Science 2020-03-10 Meng Tian , Liang Pan , Marcelo H Ang , Gim Hee Lee

Single object tracking (SOT) heavily relies on the representation of the target object as a bounding box. However, due to the potential deformation and rotation experienced by the tracked targets, the genuine bounding box fails to capture…

Computer Vision and Pattern Recognition · Computer Science 2023-09-26 Guotian Zeng , Bi Zeng , Hong Zhang , Jianqi Liu , Qingmao Wei

Accurate sound localization in a reverberation environment is essential for human auditory perception. Recently, Convolutional Neural Networks (CNNs) have been utilized to model the binaural human auditory pathway. However, CNN shows…

Sound · Computer Science 2024-08-08 Sheng Kuang , Jie Shi , Kiki van der Heijden , Siamak Mehrkanoon

In this paper, we consider an intelligent reflecting surface (IRS)-aided single-user system where an IRS with discrete phase shifts is deployed to assist the uplink communication. A practical transmission protocol is proposed to execute…

Information Theory · Computer Science 2019-12-24 Changsheng You , Beixiong Zheng , Rui Zhang

Point-source transient events (PSTEs) - optical events that are both extremely fast and extremely small - pose several challenges to an imaging system. Due to their speed, accurately characterizing such events often requires detectors with…

Machine Learning · Statistics 2025-02-13 Frank Qiu , Joshua Michalenko , Lilian K. Casias , Cameron J. Radosevich , Jon Slater , Eric A. Shields

Detecting oriented objects along with estimating their rotation information is one crucial step for analyzing remote sensing images. Despite that many methods proposed recently have achieved remarkable performance, most of them directly…

Computer Vision and Pattern Recognition · Computer Science 2021-12-02 Yanjie Wang , Xu Zou , Zhijun Zhang , Wenhui Xu , Liqun Chen , Sheng Zhong , Luxin Yan , Guodong Wang

Surround-view perception is increasingly important for robotic navigation and loco-manipulation, especially in human-in-the-loop settings such as teleoperation, data collection, and emergency takeover. However, current robotic visual…

This study presents band-ensemble Spectral Proper Orthogonal Decomposition (bSPOD). The approach is inspired by frequency smoothing, a method used to reduce estimator variance in power spectral density estimates, and is here extended to…

Approximation of scattered data is often a task in many engineering problems. The Radial Basis Function (RBF) approximation is appropriate for large scattered (unordered) datasets in d-dimensional space. This approach is useful for a higher…

Numerical Analysis · Computer Science 2018-06-21 Zuzana Majdisova , Vaclav Skala

Optimal Transport (OT) has proven effective for domain adaptation (DA) by aligning distributions across domains with differing statistical properties. Building on the approach of Courty et al. (2016), who mapped source data to the target…

Machine Learning · Statistics 2025-05-15 Brian Britos , Mathias Bourel

Recently, pseudo analog transmission has gained increasing attentions due to its ability to alleviate the cliff effect in video multicast scenarios. The existing pseudo analog systems are sorely optimized under the minimum mean squared…

Multimedia · Computer Science 2020-07-22 Xiao-Wei Tang , Xin-Lin Huang , Fei Hu , Qingjiang Shi

Subsampled Randomized Hadamard Transform (SRHT), a popular random projection method that can efficiently project a $d$-dimensional data into $r$-dimensional space ($r \ll d$) in $O(dlog(d))$ time, has been widely used to address the…

Machine Learning · Computer Science 2020-10-07 Zijian Lei , Liang Lan

Robust Affine Matching with Grassmannians (RoAM) is a new algorithm to perform affine registration of point clouds. The algorithm is based on minimizing the Frobenius distance between two elements of the Grassmannian. For this purpose, an…

Computer Vision and Pattern Recognition · Computer Science 2024-10-10 Alexander Kolpakov , Michael Werman

An orthogonal discrete auditory transform (ODAT) from sound signal to spectrum is constructed by combining the auditory spreading matrix of Schroeder et al and the time one map of a discrete nonlocal Schr\"odinger equation. Thanks to the…

Numerical Analysis · Mathematics 2007-05-23 Jack Xin , Yingyong Qi

We present the first algorithm to efficiently compute certifiably optimal solutions to range-aided simultaneous localization and mapping (RA-SLAM) problems. Robotic navigation systems increasingly incorporate point-to-point ranging sensors,…

The training of large multimodal models fundamentally relies on massive image-text datasets, which inevitably incur prohibitive computational overhead. Dataset selection offers a promising paradigm by identifying a highly informative…

Computer Vision and Pattern Recognition · Computer Science 2026-05-13 Boran Zhao , Hetian Liu , Zhenxian Hu , Yuqing Yuan , Yu Yan , Pengju Ren
‹ Prev 1 4 5 6 7 8 10 Next ›