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In this article, we address the timely topic of cellular bistatic simultaneous localization and mapping (SLAM) with specific focus on end-to-end processing solutions, from raw I/Q samples, via channel parameter estimation to user equipment…

Signal Processing · Electrical Eng. & Systems 2024-05-21 Elizaveta Rastorgueva-Foi , Ossi Kaltiokallio , Yu Ge , Matias Turunen , Jukka Talvitie , Bo Tan , Musa Furkan Keskin , Henk Wymeersch , Mikko Valkama

Robotic grasping for a diverse set of objects is essential in many robot manipulation tasks. One promising approach is to learn deep grasping models from large training datasets of object images and grasp labels. However, empirical grasping…

Robotics · Computer Science 2022-04-06 Xinghao Zhu , Yefan Zhou , Yongxiang Fan , Lingfeng Sun , Jianyu Chen , Masayoshi Tomizuka

Line intensity mapping (LIM) is a promising tool to efficiently probe the three-dimensional large-scale structure by mapping the aggregate emission of a spectral line from all sources that trace the matter density field. Spectral lines from…

Cosmology and Nongalactic Astrophysics · Physics 2020-10-09 Yun-Ting Cheng , Tzu-Ching Chang , James J. Bock

We address the problem of sparse recovery in an online setting, where random linear measurements of a sparse signal are revealed sequentially and the objective is to recover the underlying signal. We propose a reweighted least squares (RLS)…

Machine Learning · Computer Science 2017-06-30 Subhadip Mukherjee , Deepak R. , Huaijin Chen , Ashok Veeraraghavan , Chandra Sekhar Seelamantula

We introduce GeMS, a framework for 3D Gaussian Splatting (3DGS) designed to handle severely motion-blurred images. State-of-the-art deblurring methods for extreme blur, such as ExBluRF, as well as Gaussian Splatting-based approaches like…

Computer Vision and Pattern Recognition · Computer Science 2025-08-21 Gopi Raju Matta , Trisha Reddypalli , Vemunuri Divya Madhuri , Kaushik Mitra

Sparse modeling is one of the efficient techniques for imaging that allows recovering lost information. In this paper, we present a novel iterative phase-retrieval algorithm using a sparse representation of the object amplitude and phase.…

Computer Vision and Pattern Recognition · Computer Science 2011-08-17 Artem Migukin , Vladimir Katkovnik , Jaakko Astola

We propose a new algorithm for recovery of sparse signals from their compressively sensed samples. The proposed algorithm benefits from the strategy of gradual movement to estimate the positions of non-zero samples of sparse signal. We…

Information Theory · Computer Science 2012-04-04 Seyed Hossein Hosseini , Mahrokh G. Shayesteh

We present a theoretical analysis of the measuring algorithm we use when applying the Diffracto-Astrometry technique to Hubble Space Telescope Wide Field Planetary Camera 2 (WFPC2) saturated stellar images. Theoretical Point Spread…

Instrumentation and Methods for Astrophysics · Physics 2015-05-30 A. Ruelas-Mayorga , L. J. Sanchez , J. Olivares , C. Allen , A. Poveda , R. Costero , A. Nigoche-Netro

$\textbf{Aims}$. With the ever-increasing survey speed of optical wide-field telescopes and the importance of discovering transients when they are still young, rapid and reliable source localization is paramount. We present…

In the fourth \emph{Fermi} Large Area Telescope source catalog (4FGL), 5064 $\gamma$-ray sources are reported, including 3207 active galactic nuclei (AGNs), 239 pulsars, 1336 unassociated sources, 92 sources with weak association with…

High Energy Astrophysical Phenomena · Physics 2021-02-10 Kerui Zhu , Shi-Ju Kang , Yong-Gang Zheng

Relative localization is a crucial capability for multi-robot systems operating in GPS-denied environments. Existing approaches for multi-robot relative localization often depend on costly or short-range sensors like cameras and LiDARs.…

Robotics · Computer Science 2025-07-01 Sai Krishna Ghanta , Ramviyas Parasuraman

We present the source separation framework SCARLET for multi-band images, which is based on a generalization of the Non-negative Matrix Factorization to alternative and several simultaneous constraints. Our approach describes the observed…

Instrumentation and Methods for Astrophysics · Physics 2018-08-14 Peter Melchior , Fred Moolekamp , Maximilian Jerdee , Robert Armstrong , Ai-Lei Sun , James Bosch , Robert Lupton

This paper presents a new approach to the recovery of a spectrally sparse signal (SSS) from partially observed entries, focusing on challenges posed by large-scale data and heavy noise environments. The SSS reconstruction can be formulated…

Signal Processing · Electrical Eng. & Systems 2024-05-14 Xi Yao , Wei Dai

We present a dense simultaneous localization and mapping (SLAM) method that uses 3D Gaussians as a scene representation. Our approach enables interactive-time reconstruction and photo-realistic rendering from real-world single-camera RGBD…

Computer Vision and Pattern Recognition · Computer Science 2024-03-25 Vladimir Yugay , Yue Li , Theo Gevers , Martin R. Oswald

Adaptive causal representation learning from observational data is presented, integrated with an efficient sample splitting technique within the semiparametric estimating equation framework. The support points sample splitting (SPSS), a…

Machine Learning · Statistics 2024-11-25 Lynda Aouar , Han Yu

Approximate message passing algorithm enjoyed considerable attention in the last decade. In this paper we introduce a variant of the AMP algorithm that takes into account glassy nature of the system under consideration. We coin this…

Disordered Systems and Neural Networks · Physics 2019-02-07 Fabrizio Antenucci , Florent Krzakala , Pierfrancesco Urbani , Lenka Zdeborová

Restoring images degraded by spatially varying blur is a problem encountered in many disciplines such as astrophysics, computer vision or biomedical imaging. One of the main challenges to perform this task is to design efficient numerical…

Optimization and Control · Mathematics 2015-10-13 Paul Escande , Pierre Weiss

Audio-Visual Source Localization (AVSL) is the task of identifying specific sounding objects in the scene given audio cues. In our work, we focus on semi-supervised AVSL with pseudo-labeling. To address the issues with vanilla hard…

Computer Vision and Pattern Recognition · Computer Science 2024-03-06 Yuxin Guo , Shijie Ma , Yuhao Zhao , Hu Su , Wei Zou

In industrial anomaly detection, model efficiency and mobile-friendliness become the primary concerns in real-world applications. Simultaneously, the impressive generalization capabilities of Segment Anything (SAM) have garnered broad…

Computer Vision and Pattern Recognition · Computer Science 2024-11-20 Chenghao Li , Lei Qi , Xin Geng

When an agent, person, vehicle or robot is moving through an unknown environment without GNSS signals, online mapping of nonlinear terrains can be used to improve position estimates when the agent returns to a previously mapped area.…

Machine Learning · Computer Science 2025-05-22 Frida Marie Viset , Rudy Helmons , Manon Kok