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Gait Evaluation Using Procrustes and Euclidean Distance Matrix Analysis
Anwary, Arif Reza, Yu, Hongnian, Vassallo, Michael
Published in IEEE journal of biomedical and health informatics (01.09.2019)
Published in IEEE journal of biomedical and health informatics (01.09.2019)
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On the relation between graph distance and Euclidean distance in random geometric graphs
Díaz, J., Mitsche, D., Perarnau, G., Pérez-Giménez, X.
Published in Advances in applied probability (01.09.2016)
Published in Advances in applied probability (01.09.2016)
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3D CHANGE DETECTION OF POINT CLOUDS BASED ON DENSITY ADAPTIVE LOCAL EUCLIDEAN DISTANCE
Chai, J. X., Zhang, Y. S., Yang, Z., Wu, J.
Published in International archives of the photogrammetry, remote sensing and spatial information sciences. (01.01.2022)
Published in International archives of the photogrammetry, remote sensing and spatial information sciences. (01.01.2022)
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Phase Space Reconstruction and Euclidean Distance for Improving the Classification of Gait Patterns between Patients with Knee Osteoarthritis and Healthy Controls
Wu, Jumin, Peng, Zhangbo, Chen, Yang, Fang, Cheng, Yuan, Chengzhi, Zeng, Wei
Published in Chinese Control Conference (28.07.2024)
Published in Chinese Control Conference (28.07.2024)
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Modeling and classification of gait patterns between anterior cruciate ligament deficient and intact knees based on phase space reconstruction, Euclidean distance and neural networks
Wu, Wenbao, Zeng, Wei, Ma, Limin, Yuan, Chengzhi, Zhang, Yu
Published in Biomedical engineering online (01.11.2018)
Published in Biomedical engineering online (01.11.2018)
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Determination of lung segments in computed tomography images using the Euclidean distance to the pulmonary artery
Stoecker, Christina, Welter, Stefan, Moltz, Jan H., Lassen, Bianca, Kuhnigk, Jan-Martin, Krass, Stefan, Peitgen, Heinz-Otto
Published in Medical physics (Lancaster) (01.09.2013)
Published in Medical physics (Lancaster) (01.09.2013)
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Classification of gait patterns between patients with Parkinson’s disease and healthy controls using phase space reconstruction (PSR), empirical mode decomposition (EMD) and neural networks
Zeng, Wei, Yuan, Chengzhi, Wang, Qinghui, Liu, Fenglin, Wang, Ying
Published in Neural networks (01.03.2019)
Published in Neural networks (01.03.2019)
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