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Publication search results
found 36 matches
- 2023
- Azubuike Okorie, Chandra Kambhamettu, Sokratis Makrogiannis:
Unsupervised learning of probabilistic subspaces for multi-spectral and multi-temporal image-based disaster mapping. Mach. Vis. Appl. 34(6): 103 (2023) - Sanjay Ghosh, Ashish Raj, Srikantan S. Nagarajan:
A joint subspace mapping between structural and functional brain connectomes. NeuroImage 272: 119975 (2023) - Xiu Li, Chengyu Zheng, Jie Nie, Ruoyu Zhang, Xinyue Liang, Zhiqiang Wei:
Relevance and Irrelevance Considered Subspace Mapping Neural Networks for Remote Sensing Text-Image Retrieval. MMAsia 2023: 21:1-21:7 - Calder D. Sheagren, Brenden T. Kadota, Jaykumar H. Patel, Mark Chiew, Graham A. Wright:
Accelerated Cardiac Parametric Mapping Using Deep Learning-Refined Subspace Models. STACOM@MICCAI 2023: 369-379 - 2022
- Jin Cui, Xuanyu Jin, Hua Hu, Li Zhu, Kenji Ozawa, Gang Pan, Wanzeng Kong:
Dynamic Distribution Alignment With Dual-Subspace Mapping for Cross-Subject Driver Mental State Detection. IEEE Trans. Cogn. Dev. Syst. 14(4): 1705-1716 (2022) - Cassie Meeker, Maximilian Haas-Heger, Matei T. Ciocarlie:
A Continuous Teleoperation Subspace With Empirical and Algorithmic Mapping Algorithms for Nonanthropomorphic Hands. IEEE Trans Autom. Sci. Eng. 19(1): 373-386 (2022) - Panagiotis Fountas, Maria Papathanasaki, Kostas Kolomvatsos, Christos Anagnostopoulos:
Query Driven Data Subspace Mapping. AIAI (2) 2022: 496-508 - Azubuike Okorie, Sokratis Makrogiannis:
Subspace Analysis for Multi-temporal Disaster Mapping Using Satellite Imagery. ISVC (1) 2022: 162-173 - 2021
- Mengying Xie, Zehui Ye, Gan Pan, Xiaolan Liu:
Incomplete multi-view subspace clustering with adaptive instance-sample mapping and deep feature fusion. Appl. Intell. 51(8): 5584-5597 (2021) - 2020
- Amirhosein Mosavi, Ataollah Shirzadi, Bahram Choubin, Fereshteh Taromideh, Farzaneh Sajedi Hosseini, Moslem Borji, Himan Shahabi, Aryan Salvati, Adrienn Dineva:
Towards an Ensemble Machine Learning Model of Random Subspace Based Functional Tree Classifier for Snow Avalanche Susceptibility Mapping. IEEE Access 8: 145968-145983 (2020) - Viet-Ha Nhu, Phuong-Thao Thi Ngo, Tien Dat Pham, Jie Dou, Xuan Song, Nhat-Duc Hoang, An Dang Tran, Phan Cao Duong, Ibrahim Berkan Aydilek, Mahdis Amiri, Romulus Costache, Pham Viet Hoa, Dieu Tien Bui:
A New Hybrid Firefly-PSO Optimized Random Subspace Tree Intelligence for Torrential Rainfall-Induced Flash Flood Susceptible Mapping. Remote. Sens. 12(17): 2688 (2020) - Volkert Roeloffs, Martin Uecker, Jens Frahm:
Joint T1 and T2 Mapping With Tiny Dictionaries and Subspace-Constrained Reconstruction. IEEE Trans. Medical Imaging 39(4): 1008-1014 (2020) - Fotios D. Mandanas, Constantine Kotropoulos:
Subspace Learning and Feature Selection via Orthogonal Mapping. IEEE Trans. Signal Process. 68: 1034-1047 (2020) - 2019
- Eden Fedida Hefetz, Edward Chien, Ofir Weber:
A Subspace Method for Fast Locally Injective Harmonic Mapping. Comput. Graph. Forum 38(2): 105-119 (2019) - Lingyan Fan, Wuyi Sun, Guorui Feng:
Image Steganalysis via Random Subspace Fisher Linear Discriminant Vector Functional Link Network and Feature Mapping. Mob. Networks Appl. 24(4): 1269-1278 (2019) - Paul K. Han, Debra E. Horng, Thibault Marin, Yoann Petibon, Jinsong Ouyang, Georges El Fakhri, Chao Ma:
Free-Breathing Three-Dimensional T1 Mapping of the Heart Using Subspace-Based Data Acquisition and Image Reconstruction. EMBC 2019: 4008-4011 - Rodrigo A. Ricco, Bruno Otávio Soares Teixeira:
Mapping prior information onto LMI eigenvalue-regions for discrete-time subspace identification. CoRR abs/1904.05959 (2019) - Cassie Meeker, Maximilian Haas-Heger, Matei T. Ciocarlie:
A Continuous Teleoperation Subspace with Empirical and Algorithmic Mapping Algorithms for Non-Anthropomorphic Hands. CoRR abs/1911.09565 (2019) - 2018
- Peiyuan Liao:
Deep Neural Network Based Subspace Learning of Robotic Manipulator Workspace Mapping. CoRR abs/1804.08951 (2018) - 2017
- Takeshi Iwashita, Shigeru Kawaguchi, Takeshi Mifune, Tetsuji Matsuo:
Automatic mapping operator construction for subspace correction method to solve a series of linear systems. JSIAM Lett. 9: 25-28 (2017) - 2016
- Niclas Niclas, David Gustafsson:
Non-Linear Hyperspectral Subspace Mapping using Stacked Auto-Encoder. SAIS 2016: 129:001 - 2015
- Nicholas Johnson, Huanan Zhang, Gang Fang, Vipin Kumar, Rui Kuang:
SubPatCNV: approximate subspace pattern mining for mapping copy-number variations. BMC Bioinform. 16: 16:1-16:12 (2015) - 2013
- Christine Guillemot, Mehmet Türkan, Olivier Le Meur, Mounira Ebdelli:
Image inpainting using LLE-LDNR and linear subspace mappings. ICASSP 2013: 1558-1562 - 2012
- Malin Björnsdotter Åberg, Johan Wessberg:
Clustered sampling improves random subspace brain mapping. Pattern Recognit. 45(6): 2035-2040 (2012) - Nicholas Johnson, Gang Fang, Rui Kuang:
Approximate subspace pattern mining for mapping copy-number variations. BCB 2012: 616 - Jano Malvar, Alejandro G. Yepes, Ana Vidal, Pablo Fernandez-Comesana, Francisco D. Freijedo, Óscar Lopez, Jesús Doval-Gandoy:
Harmonic subspace and sequence mapping in a series-connected six-phase two-motor drive. IECON 2012: 3622-3627 - 2011
- Axel J. Soto, Marc Strickert, Gustavo E. Vazquez, Evangelos E. Milios:
Subspace Mapping of Noisy Text Documents. Canadian AI 2011: 377-383 - Malin Björnsdotter, Johan Wessberg:
Comparing Clustered and Distributed Sampling for Random Subspace Brain Mapping. PRNI 2011: 29-32 - 2010
- Diego Sona, Paolo Avesani:
Feature Rating by Random Subspaces for Functional Brain Mapping. Brain Informatics 2010: 112-123 - Diego Sona, Paolo Avesani:
Multivariate Brain Mapping by Random Subspaces. ICPR 2010: 2576-2579
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