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Asynchronous Collaborative Localization by Integrating Spatiotemporal Graph Learning with Model-Based Estimation
[article]
2021
arXiv
pre-print
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In this paper, we introduce a novel approach that integrates uncertainty-aware spatiotemporal graph learning and model-based state estimation for a team of robots to collaboratively localize objects. ...
Moreover, we propose a novel method for integrated learning and model-based state estimation, which fuses asynchronous observations obtained from an arbitrary number of robots for collaborative localization ...
Then, we introduce a method to integrate spatiotemporal graph learning and model-based estimation for asynchronous collaborative object localization. ...
arXiv:2111.03751v1
fatcat:tcjfvqq4qnabrmo7sjhd5vm2ze
Towards better traffic volume estimation: Jointly addressing the underdetermination and nonequilibrium problems with correlation-adaptive GNNs
[article]
2023
arXiv
pre-print
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graph attention is developed and integrated into the graph convolution process, to capture non-local correlations between sensors. ...
Here we demonstrate a graph-based deep learning method that can offer a data-driven, model-free and correlation adaptive approach to tackle the above issues and perform accurate network-wide traffic volume ...
Acknowledgement This research was sponsored by the National Natural Science Foundation of China ( 52125208 ...
arXiv:2303.05660v3
fatcat:i7fyukk5xzcxlpltqxi5ltmqny
A Survey on Federated Learning in Intelligent Transportation Systems
[article]
2024
arXiv
pre-print
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2024 pre-print arXiv:2403.07444v1 fatcat:mqjddmpddveujpugmbbhnvl3ru
To address these limitations, federated learning (FL) has been proposed as a promising solution. ...
However, most current ITS applications rely on a centralized training approach where users upload source data to a cloud server with high computing power for management and centralized training. ...
Target Recognition [35] Propose an asynchronous federated aggregation protocol to select the most optimal local models based on the quality of each model. ...
arXiv:2403.07444v2
fatcat:nya5t3utlvhg5aftnarshtsasi
GCCE 2020 Subject Index
2020
2020 IEEE 9th Global Conference on Consumer Electronics (GCCE)
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Neural Network for Few Shot Classification
Self-Attention Based Neural Network for Few Shot Classification
Separation of Multiple Sound Sources in the Same Direction by Instantaneous Spectral Estimation ...
Separation of Multiple Sound Sources in the Same Direction by Instantaneous Spectral Estimation
Sequence-To-One Neural Networks for Japanese Dialect Speech Classification ...
in Team Sports Transfer Learning Model for Image Segmentation by Integrating U-Net++ and SE Block Transfer Learning Model for Image Segmentation by Integrating U-Net++ and SE Block Transmitter Control ...
doi:10.1109/gcce50665.2020.9291796
fatcat:bmnnn7xnxrefhaneq262fe4i6u
2019 Index IEEE Transactions on Systems, Man, and Cybernetics: Systems Vol. 49
2019
IEEE Transactions on Systems, Man & Cybernetics. Systems
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., +, TSMC Dec. 2019 2536-2547 Incremental Spatiotemporal Learning for Online Modeling of Distributed Parameter Systems. ...
Ji, P., +,
TSMC Oct. 2019 1993-2004
Computational modeling
Incremental Spatiotemporal Learning for Online Modeling of Distributed
Parameter Systems. ...
doi:10.1109/tsmc.2019.2956665
fatcat:xhplbanlyne7nl7gp2pbrd62oi
2020 Index IEEE Transactions on Cybernetics Vol. 50
2020
IEEE Transactions on Cybernetics
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., +, TCYB Sept. 2020 4121-4131 Reinforcement Learning-Based Optimal Sensor Placement for Spatiotemporal Modeling. ...
., +, TCYB July 2020 3182-3194 Consensus-Based Odor Source Localization by Multiagent Systems Under Resource Constraints. ...
Stock markets A Quantum-Inspired Similarity Measure for the Analysis of Complete Weighted Graphs. Bai, L., +, TCYB March 2020 1264 -1277 ...
doi:10.1109/tcyb.2020.3047216
fatcat:5giw32c2u5h23fu4drupnh644a
2021 Index IEEE Transactions on Cybernetics Vol. 51
2021
IEEE Transactions on Cybernetics
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The primary entry includes the coauthors' names, the title of the paper or other item, and its location, specified by the publication abbreviation, year, month, and inclusive pagination. ...
., +, TCYB Feb. 2021 1043-1055 Fast Online Video Pose Estimation by Dynamic Bayesian Modeling of Mode Transitions. ...
Tom, A.J., +, TCYB Feb. 2021 1004-1014 Fast Online Video Pose Estimation by Dynamic Bayesian Modeling of Mode Transitions. ...
doi:10.1109/tcyb.2021.3139447
fatcat:myjx3olwvfcfpgnwvbuujwzyoi
Knowledge discovery from sensor data (SensorKDD)
2008
SIGKDD Explorations
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culminated into the organization of Sensor-KDD series of workshops in conjunction with the prestigious ACM SIGKDD International Conference of Knowledge Discovery and Data Mining. ...
Keeping in view the requirements of the emerging field of knowledge discovery from sensor data, we took initiative to develop a community of researchers with common interests and scientific goals, which ...
This workshop report has been co-authored by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the U.S. Department of Energy. ...
doi:10.1145/1540276.1540297
fatcat:72jirtrxibbrpmpfcwrivmedjm
Knowledge discovery from sensor data (SensorKDD)
2010
SIGKDD Explorations
Preserved Fulltext
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culminated into the organization of Sensor-KDD series of workshops in conjunction with the prestigious ACM SIGKDD International Conference of Knowledge Discovery and Data Mining. ...
Keeping in view the requirements of the emerging field of knowledge discovery from sensor data, we took initiative to develop a community of researchers with common interests and scientific goals, which ...
This workshop report has been co-authored by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the U.S. Department of Energy. ...
doi:10.1145/1809400.1809417
fatcat:jrtrixjfzzgo3bdlelcyldihom
Table of Contents
2021
IEEE Signal Processing Letters
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Zhang GraphTTE: Travel Time Estimation Based on Attention-Spatiotemporal Graphs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ...
Kellermann Local Graph Clustering With Network Lasso . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A. Jung and Y. ...
doi:10.1109/lsp.2021.3134549
fatcat:m6obtl7k7zdqvd62eo3c4tptfy
Table of Contents
2020
IEEE Robotics and Automation Letters
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Kanehiro 6371 Multi-Contact Locomotion Planning for Humanoid Robot Based on Sustainable Contact Graph With Local Contact Modification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . I. ...
Azaria 6185 Cluster-based Penalty Scaling for Robust Pose Graph Optimization .
Robotic Deep Rolling With Iterative Learning Motion and Force Control . . . Q. Zou, M. Cong, D. Liu, Y. Du, and Z. ...
doi:10.1109/lra.2020.3030731
fatcat:kwx4xyitfbfuzgugbi5vavx2xu
Table of Contents
2021
IEEE Signal Processing Letters
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Li GraphTTE: Travel Time Estimation Based on Attention-Spatiotemporal Graphs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ...
Yuan Local Graph Clustering With Network Lasso . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A. Jung and Y. ...
doi:10.1109/lsp.2021.3134551
fatcat:ab4b4tb5rrcu5cq6aifdekrizq
Single-pixel interior filling function approach for detecting and correcting errors in particle tracking
2016
Proceedings of the National Academy of Sciences of the United States of America
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Distributed cooperative output regulation controllers depending on local states and neighboring inputs are presented, which are designed by combining feedback passivity theories and the internal model ...
We exploit reduced-dimension beamspace channel state information (CSI) given by compressive sensing (CS) based channel estimators. ...
Motivated by these observations, we propose a deep learning framework, which simultaneously performs deep feature learning for visual representation in conjunction with spatiotemporal context modeling. ...
doi:10.1073/pnas.1619104114
pmid:28028226
pmcid:PMC5240672
fatcat:imzi4n3bmjguzjakwdalknvkmi
Collaborative Perception in Autonomous Driving: Methods, Datasets and Challenges
[article]
2023
arXiv
pre-print
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2023 pre-print arXiv:2301.06262v1 fatcat:ctp7corjyjbojhllzojueianrmOther Versions
We start with a brief overview of collaboration schemes. After that, we systematically summarize the collaborative perception methods for ideal scenarios and real-world issues. ...
So far, however, few reviews have focused on systematical collaboration modules and large-scale collaborative perception datasets. ...
Therefore, we introduce graph-based collaboration methods based on these two stages. Wang et al. ...
arXiv:2301.06262v4
fatcat:sihpwiebubfslhqw6tf7ovgicu
Spatiotemporal Data Mining: A Survey on Challenges and Open Problems
[article]
2021
arXiv
pre-print
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Moreover, we discuss the limitations in the literature and open research problems related to spatiotemporal data representations, modelling and visualisation, and comprehensiveness of approaches. ...
We attempt to fill this gap by providing a comprehensive literature survey on state-of-the-art advances in STDM. ...
The authors in [220] proposed LIME (Local Interpretable Modelagnostic Explainations), a method that explains model predictions by learning an interpretable model locally around the predictions. ...
arXiv:2103.17128v1
fatcat:ci5pt5bytndr5inolznjsaizpi
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