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Publication search results
found 78 matches
- 2023
- Feng Han, Tao Liang, Jiping Ren, Yuan Li:
Automated Extraction of Rail Point Clouds by Multi-Scale Dimensional Features From MLS Data. IEEE Access 11: 32427-32436 (2023) - Chen Zhao, Shichang Du, Jun Lv, Yafei Deng, Guilong Li:
A novel parallel classification network for classifying three-dimensional surface with point cloud data. J. Intell. Manuf. 34(2): 515-527 (2023) - Andreas Anastasiou, Angelos Papanastasiou:
Generalized multiple change-point detection in the structure of multivariate, possibly high-dimensional, data sequences. Stat. Comput. 33(5): 94 (2023) - Ruiyu Xu, Jianguo Wu, Xiaowei Yue, Yongxiang Li:
Online Structural Change-Point Detection of High-dimensional Streaming Data via Dynamic Sparse Subspace Learning. Technometrics 65(1): 19-32 (2023) - Wanrong Zhang, Yajun Mei:
Bandit Change-Point Detection for Real-Time Monitoring High-Dimensional Data Under Sampling Control. Technometrics 65(1): 33-43 (2023) - Frederiek Wesel, Kim Batselier:
Tensor-based Kernel Machines with Structured Inducing Points for Large and High-Dimensional Data. AISTATS 2023: 8308-8320 - Koki Yoshioka, Gen Niina, Hiroshi Dozono:
The Method of Making the Low-dimensional Map that Preserves the Distance Relationships from Selected Data Point. IRI 2023: 166-172 - 2022
- Rami Katz, Emilia Fridman:
Sampled-data finite-dimensional boundary control of 1D parabolic PDEs under point measurement via a novel ISS Halanay's inequality. Autom. 135: 109966 (2022) - Martin Donati:
Two-Dimensional Point Vortex Dynamics in Bounded Domains: Global Existence for Almost Every Initial Data. SIAM J. Math. Anal. 54(1): 79-113 (2022) - Lynna Chu, Hao Chen:
Sequential Change-Point Detection for High-Dimensional and Non-Euclidean Data. IEEE Trans. Signal Process. 70: 4498-4511 (2022) - Lynna Chu, Hao Chen:
Corrections to "Sequential Change-Point Detection for High-Dimensional and Non-Euclidean Data". IEEE Trans. Signal Process. 70: 5765 (2022) - Joyce A. Chew, Holly R. Steach, Siddharth Viswanath, Hau-Tieng Wu, Matthew J. Hirn, Deanna Needell, Matthew D. Vesely, Smita Krishnaswamy, Michael Perlmutter:
The Manifold Scattering Transform for High-Dimensional Point Cloud Data. TAG-ML 2022: 67-78 - Kamil Faber, Roberto Corizzo, Bartlomiej Sniezynski, Michael Baron, Nathalie Japkowicz:
WATCH: Wasserstein Change Point Detection for High-Dimensional Time Series Data. CoRR abs/2201.07125 (2022) - Joyce A. Chew, Holly R. Steach, Siddharth Viswanath, Hau-Tieng Wu, Matthew J. Hirn, Deanna Needell, Smita Krishnaswamy, Michael Perlmutter:
The Manifold Scattering Transform for High-Dimensional Point Cloud Data. CoRR abs/2206.10078 (2022) - Ryan Cotsakis:
Identifying the reach from high-dimensional point cloud data with connections to r-convexity. CoRR abs/2212.01013 (2022) - 2021
- Yongzhi Wang, Wenlong Tu, Hui Li:
Fragmentation calculation method for blast muck piles in open-pit copper mines based on three-dimensional laser point cloud data. Int. J. Appl. Earth Obs. Geoinformation 100: 102338 (2021) - Preeti, Anurag Jayswal, Manuel Arana-Jiménez:
Robust saddle-point criteria for multi-dimensional control optimisation problems with data uncertainty. Int. J. Control 94(12): 3288-3299 (2021) - Taehoon Kim, Jun Lee, Kyoung-Sook Kim, Akiyoshi Matono, Ki-Joune Li:
Utilizing extended geocodes for handling massive three-dimensional point cloud data. World Wide Web 24(4): 1321-1344 (2021) - Yu-Chen Chou, Yen-Po Lin, Yang-Ming Yeh, Yi-Chang Lu:
3D-GFE: a Three-Dimensional Geometric-Feature Extractor for Point Cloud Data. APSIPA ASC 2021: 2013-2017 - Kamil Faber, Roberto Corizzo, Bartlomiej Sniezynski, Michael Baron, Nathalie Japkowicz:
WATCH: Wasserstein Change Point Detection for High-Dimensional Time Series Data. IEEE BigData 2021: 4450-4459 - Sabrina De Capitani di Vimercati, Dario Facchinetti, Sara Foresti, Gianluca Oldani, Stefano Paraboschi, Matthew Rossi, Pierangela Samarati:
Multi-dimensional indexes for point and range queries on outsourced encrypted data. GLOBECOM 2021: 1-6 - Zhonghua Su, Guiyun Zhou, Lihui Song, Xukun Lu, Rong Zhao, Xiang Zhou:
Three-Dimensional Reconstruction of Leaves Based on Laser Point Cloud Data. IGARSS 2021: 6688-6691 - Lucas Magee, Yusu Wang:
Graph skeletonization of high-dimensional point cloud data via topological method. CoRR abs/2109.07606 (2021) - 2020
- Khadidja Henni, Pierre-Yves Louis, Brigitte Vannier, Ahmed Moussa:
Is-ClusterMPP: clustering algorithm through point processes and influence space towards high-dimensional data. Adv. Data Anal. Classif. 14(3): 543-570 (2020) - Ieva Dauzickaite, Amos S. Lawless, Jennifer A. Scott, Peter Jan van Leeuwen:
Spectral estimates for saddle point matrices arising in weak constraint four-dimensional variational data assimilation. Numer. Linear Algebra Appl. 27(5) (2020) - Ruiyu Xu, Jianguo Wu, Xiaowei Yue, Yongxiang Li:
Online Structural Change-point Detection of High-dimensional Streaming Data via Dynamic Sparse Subspace Learning. CoRR abs/2009.11713 (2020) - 2019
- Stefan Kufer:
Effective and Efficient Summarization of Two-Dimensional Point Data: Approaches for Resource Description and Selection in Spatial Application Scenarios. University of Bamberg, Germany, 2019, ISBN 978-3-86309-672-4, pp. 1-501 - Oliver Chikumbo, Vincent Granville:
Optimal Clustering and Cluster Identity in Understanding High-Dimensional Data Spaces with Tightly Distributed Points. Mach. Learn. Knowl. Extr. 1(2): 715-744 (2019) - Nishant Ravikumar, Ali Gooya, Leandro Beltrachini, Alejandro F. Frangi, Zeike A. Taylor:
Generalised coherent point drift for group-wise multi-dimensional analysis of diffusion brain MRI data. Medical Image Anal. 53: 47-63 (2019) - Erik Næsset, Terje Gobakken, Ronald E. McRoberts:
A Model-Dependent Method for Monitoring Subtle Changes in Vegetation Height in the Boreal-Alpine Ecotone Using Bi-Temporal, Three Dimensional Point Data from Airborne Laser Scanning. Remote. Sens. 11(15): 1804 (2019)
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