Automated recognition of robotic manipulation failures in high-throughput biodosimetry tool

Expert Systems with Applications

Volumn 39, Issue 10, 2012, Pages 9602-9611

  Chen, Youhua ^a   Wang, Hongliang ^a   Zhang, Jian ^a   Garty, Guy ^b   Simaan, Nabil ^a   Lawrence Yao, Y ^a   Brenner, David J ^b  

^a Columbia University ^*  (United States)

^b Och Spine at New York Presbyterian Hospitals   (United States)

Author keywords

Biodosimetry automation; Classification; Failure recognition; Feature extraction; Robotic manipulation

Indexed keywords

AUTOMATED RECOGNITION; BIODOSIMETRY; BLOOD SAMPLES; CLASSIFICATION METHODS; COLUMBIA UNIVERSITY; COMPUTATION COSTS; DATA PREPROCESSING; DISCRIMINATION ANALYSIS; ERROR RATE; FAILURE PROBLEMS; FEATURE SPACE; FISHER DISCRIMINATION; FISHER LINEAR DISCRIMINATIONS; HIGH-THROUGHPUT; MINIMALLY INVASIVE; PRINCIPAL COMPONENT ANALYSIS (PCA); RAW SIGNALS; REAL TIME RECOGNITION; RECOGNITION METHODS; ROBOTIC MANIPULATION; SEPARABILITY INDEX; SUPPORT VECTOR MACHINE (SVM);

AUTOMATION; CLASSIFICATION (OF INFORMATION); FEATURE EXTRACTION; MOLECULAR BIOLOGY; PRINCIPAL COMPONENT ANALYSIS; SUPPORT VECTOR MACHINES;

ROBOTICS;

EID: 84862796388     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2012.02.145     Document Type: Article

References (16)

1. F. Akbaryan, and P.R. Bishnoi Fault diagnosis of multivariate systems using pattern recognition and multisensor data analysis technique Computers & Chemical Engineering 25 9-10 2001 1313 1339
2. P.N. Belhumeur, J.P. Hespanha, and D.J. Kriegman Eigenfaces vs. Fisherfaces recognition using class specific linear projection IEEE Transactions on Pattern Analysis, and Machine Intelligence 19 7 1997 711 720
3. E.J. Bredensteiner, and K.P. Bennett Multicategory classification by support vector machines Computational Optimization and Applications 12 1-3 1999 53 79
4. C.J.C. Burges A tutorial on Support Vector Machines for pattern recognition Data Mining and Knowledge Discovery 2 2 1998 121 167
5. Chandrababu, S.; Christensen, H. I. (2009). Adding diagnostics to intelligent robot systems. In IEEE/RSJ International Conference on Intelligent Robots and Systems, 2009, IROS 2009.
6. O. Chapelle Choosing multiple parameters for support vector machines Machine Learning 46 1-3 2002 131 159
7. Y. Chen Development of a robotically-based automated biodosimetry tool for high-throughput radiological triage International Journal of Biomechatronics and Biomedical Robotics 1 2 2010 115 125
8. H.-W. Cho Identification of contributing variables using kernel-based discriminant modeling and reconstruction Expert Systems with Applications 33 2 2007 274 285
9. Duda, R. O.; Hart, P. E.; Stork, D. G. (2001). Pattern classification. (2nd ed.). New York: Wiley; p. xx, 654.
10. K. Fukunaga Introduction to statistical pattern recognition Computer science and scientific computing 1990 Academic Press Boston
11. A.M. Martinez, and A.C. Kak PCA versus LDA IEEE Transactions on Pattern Analysis and Machine Intelligence 23 2 2001 228 233
12. Mika, S.; et al. (1999). Fisher discriminant analysis with kernels. In Neural Networks for Signal Processing IX, 1999. Proceedings of the 1999 IEEE Signal Processing Society, Workshop.
13. T.C. Pellmar, and S. Rockwell Priority list of research areas for radiological nuclear threat countermeasures Radiation Research 163 1 2009 115 123
14. S. Theodoridis, and K. Koutroumbas Pattern recognition 3rd ed. 2006 Elsevier/Academic Press Amsterdam, Boston xvi, 837
15. V. Venkatasubramanian A review of process fault detection and diagnosis Part III: Process history based methods Computers & Chemical Engineering 27 3 2003 327 346
16. H. Wakaki Comparison of linear and quadratic discriminant functions Biometrika 77 1 1990 227 229