Publications related to Probabilistic Data Association for Semantic SLAM at Scale

Related publications (30)

Network Alignment With Holistic Embeddings

Quoc Viet Hung Nguyen, Thành Tâm Nguyên, Chi Thang Duong, Thanh Trung Huynh

Network alignment is the task of identifying topologically and semantically similar nodes across (two) different networks. It plays an important role in various applications ranging from social network analysis to bioinformatic network interactions. Howeve ...

IEEE COMPUTER SOC2023

A Stand-Alone Augmented Reality Intervention for Chronic Pain using Embodied Systolic Stimulation

Andrea Serino, Robert Leeb, Oliver Alan Kannape, Skander Mensi, Sylvain Cardin

Chronic pain presents a tremendous personal, societal, and financial burden. Treatment options are often limited to managing symptoms as opposed to treating the causes, and the consequences of pharmacological treatments can be immensely harmful as evidence ...

IEEE2023

Distributed Shadow Dynamic Consensus Optimization Framework for Power Market with Parameterization Bidding Strategy of GENCOs

Liying Yu, Sidi-Rachid Cherkaoui

This paper presents a distributed shadow dynamic consensus (DSDC) framework to address the generation company (GENCO) strategic bidding problem in the independent system operator (ISO) operation. First, each sub-group is defined according to the communicat ...

IEEE2023

Event-based sampled ECG morphology reconstruction through self-similarity

David Atienza Alonso, Giovanni Ansaloni, Tomas Teijeiro Campo, Silvio Zanoli

Background and Objective: Event-based analog-to-digital converters allow for sparse bio-signal acquisition, enabling local sub-Nyquist sampling frequency. However, aggressive event selection can cause the loss of important bio-markers, not recoverable with ...

2023

Upper part-load instability in a reduced-scale Francis turbine: an experimental study

François Avellan, Elena Vagnoni, Andres Müller, Ali Amini

Francis turbines with medium or high specific speeds may experience a particular type of instability in the upper part load in which the precessing vortex has an elliptical shape. The occurrence of the upper part-load instability (UPLI) is accompanied by l ...

SPRINGER2023

Lithium-niobate-based narrow-linewidth frequency agile integrated lasers with petahertz frequency tuning rate

Tobias Kippenberg, Junqiu Liu, Rui Ning Wang, Johann Emmeram Riemensberger, Anat Siddharth, Guanhao Huang, Mikhail Churaev, Viacheslav Snigirev

We demonstrate an electro-optically tunable hybrid integrated laser self-injection locked to a mode of a heterogeneously integrated lithium-niobate-on-Damascene-silicon-nitride microresonator. An intrinsic linewidth of 3 kHz and a frequency tuning rate of ...

IEEE2023

Filter-Informed Spectral Graph Wavelet Networks for Multiscale Feature Extraction and Intelligent Fault Diagnosis

Olga Fink

Intelligent fault diagnosis has been increasingly improved with the evolution of deep learning (DL) approaches. Recently, the emerging graph neural networks (GNNs) have also been introduced in the field of fault diagnosis with the goal to make better use o ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

Automatic Body Segment and Side Recognition of an Inertial Measurement Unit Sensor during Gait

Kamiar Aminian, Xavier Crevoisier, Robin Martin, Mina Arabbaniasad

Inertial measurement unit (IMU) sensors are widely used for motion analysis in sports and rehabilitation. The attachment of IMU sensors to predefined body segments and sides (left/right) is complex, time-consuming, and error-prone. Methods for solving the ...

MDPI2023

From Nano to Macro An overview of the IEEE Bio Image and Signal Processing Technical Committee

Michaël Unser, Dimitri Nestor Alice Van De Ville, Michael Stefan Daniel Liebling

The Bio Image and Signal Processing (BISP) Technical Committee (TC) of the IEEE Signal Processing Society (SPS) promotes activities within the broad technical field of biomedical image and signal processing. Areas of interest include medical and biological ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

Data Domotopia: introduction to the quantitative survey

Vincent Kaufmann, Luca Giovanni Pattaroni, Guillaume Simon Joseph Drevon, Marc-Edouard Baptiste Grégoire Schultheiss, Fiona Ines Del Puppo

This paper describes the Data Domotopia a 2300 + respondent self-administered webbased survey. It includes 100 + multi-purpose items about home-making and stillness in a moving world. We suppose that home-making can reveal coping strategies and resilience ...

2023

Reinforced polypyrrole with 2D graphene flakes decorated with interconnected nickel-tungsten metal oxide complex toward superiorly stable supercapacitor (vol 418, 129396, 2021)

Ulf Anders Hagfeldt

ELSEVIER SCIENCE SA2023

Dual-Polarized SIW Slot Antenna Using ENZ Metamaterial for 5G and mmWave Applications

Romain Christophe Rémy Fleury, Amir Jafargholi

This paper presents a broadband dual-polarized substrate integrated waveguide (SIW) slot antenna. It is analytically shown that by decreasing the permittivity of a dielectricloaded slot antenna, the resulting bandwidth increases significantly, where the wi ...

IEEE2023

Towards a pattern language for complex-mode mission concept generation

Jean-Paul Richard Kneib, Jeffrey Huang, Anne-Marlene Rüede

New space mission profiles arise from the convergence of reduced launch prices, miniaturization of electronics and the maturation of on-orbit servicing technologies. Additionally, a shift towards challenging Lunar objectives pushes for interconnected and c ...

PERGAMON-ELSEVIER SCIENCE LTD2023

Wear behaviour of novel copper alloy as an alternative to copper-beryllium

Roland Logé, Stefano Mischler, Anna Neus Igual Muñoz, Baptiste Thomas Jean Rouxel

Copper beryllium age hardenable alloys (Cu-Be) are widely used and appreciated for combining exceptional mechanical and electrical properties. However, the toxicity of these alloys pushes the scientific community to develop alternative alloys. Cu-Ni-Sn all ...

ELSEVIER SCIENCE SA2023

Quantization for Decentralized Learning Under Subspace Constraints

Ali H. Sayed, Stefan Vlaski, Roula Nassif

In this article, we consider decentralized optimization problems where agents have individual cost functions to minimize subject to subspace constraints that require the minimizers across the network to lie in low-dimensional subspaces. This constrained fo ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

Chlorination of amides: Kinetics and mechanisms of formation of N-chloramides and their reactions with phenolic compounds

Urs von Gunten, Tianqi Zhang

Amides are common constituents in natural organic matter and synthetic chemicals. In this study, we investi-gated kinetics and mechanisms of the reactions of chlorine with seven amides, including acetamide, N-meth-ylformamide, N-methylacetamide, benzamide, ...

2023

Abundant nitrogen oxide and weakly acidic environment synergistically promote daytime particulate nitrate pollution

Athanasios Nenes

Nitrate is formed through the chemical production of gas-phase nitric acid and subsequent partitioning to the aerosol phase during the daytime. Many studies in the past separated these two aspects, even though they occur simultaneously in the atmosphere. T ...

ELSEVIER2023

Pore-pressure coefficients for unsaturated soils: generalized effective stress approach

Lyesse Laloui, Alessio Ferrari, Angelica Tuttolomondo

Geotechnical problems with total stress changes occurring rapidly relative to the soil consolidation time can be conveniently addressed using an effective stress-based approach. For saturated states, analytical formulations of pore-pressure coefficients ad ...

CANADIAN SCIENCE PUBLISHING2023

A Large-Scale Characterization of How Readers Browse Wikipedia

Robert West, Tiziano Piccardi, Akhil Arora

Despite the importance and pervasiveness of Wikipedia as one of the largest platforms for open knowledge, surprisingly little is known about how people navigate its content when seeking information. To bridge this gap, we present the first systematic large ...

ASSOC COMPUTING MACHINERY2023

Machine-learning predictor of nerve fiber firing rate allows the automatic optimization of electrical stimulation protocols

Silvestro Micera, Simone Romeni, Gabriele Marino

Computational models have been widely employed to study the electrical stimulation of the nervous system. Still, most applications either study fundamental mechanisms underlying stimulation, or address qualitative scientific questions. When quantitative qu ...

IEEE2023