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A Fast Compression Framework Based on 3D Point Cloud Data for Telepresence 期刊论文
International Journal of Automation and Computing, 2020, 卷号: 17, 期号: 6, 页码: 855-866
作者:  Zun-Ran Wang;  Chen-Guang Yang;  Shi-Lu Dai
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3D point cloud compression  motion estimation  signatures of histograms orientation  3D point cloud matching  predicted frame and intra frame.  
Spectral-spatial Classification of Hyperspectral Images Using Signal Subspace Identification and Edge-preserving Filter 期刊论文
International Journal of Automation and Computing, 2020, 卷号: 17, 期号: 2, 页码: 222-232
作者:  Negin Alborzi;  Fereshteh Poorahangaryan;  Homayoun Beheshti
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Hyperspectral image  remote sensing  the hyperspectral signal subspace identification (HYSIME)  edge-preserving filter  classification  support vector machine.  
Electronic Nose and Its Applications: A Survey 期刊论文
International Journal of Automation and Computing, 2020, 卷号: 17, 期号: 2, 页码: 179-209
作者:  Diclehan Karakaya;  Oguzhan Ulucan;  Mehmet Turkan
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Artificial intelligence  machine learning  pattern recognition  electronic nose (EN)  sensors technology.  
Remote Sensing Image Registration Based on Improved KAZE and BRIEF Descriptor 期刊论文
International Journal of Automation and Computing, 2020, 卷号: 17, 期号: 4, 页码: 588-598
作者:  Huan Liu;  Gen-Fu Xiao
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Remote sensing image  image registration  composite nonlinear diffusion filter  binary code string  multi-scale pyramid space.  
Ground-level Ozone Prediction Using Machine Learning Techniques: A Case Study in Amman, Jordan 期刊论文
International Journal of Automation and Computing, 2020, 卷号: 17, 期号: 5, 页码: 667-677
作者:  Maryam Aljanabi;  Mohammad Shkoukani;  Mohammad Hijjawi
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Ozone prediction  machine learning  neural networks  supervised learning  regression.  
DiscoStyle: Multi-level Logistic Ranking for Personalized Image Style Preference Inference 期刊论文
International Journal of Automation and Computing, 2020, 卷号: 17, 期号: 5, 页码: 637-651
作者:  Zhen-Wei He;  Lei Zhang;  Fang-Yi Liu
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Facial preference  feature representation  logistic regression  face recommendation  transfer learning.