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Intelligent Segmentation of Medical Images Using Fuzzy Bitplane Thresholding

., Luo, S. (2010). A novel method for blood vessel detection from retinal images. BioMedical Engineering OnLine, 9 (1), 2-10. [13] Gunadi, W.N., Shamsuddin, S.M., Alias, R.A., Sap, M.N. (2003). Selection of defuzzification method to obtain crisp value for representing uncertain data in a modified sweep algorithm. Journal of Computer Science & Technology, 3 (2), 22-28. [14] Lopes, N.V., Mogadouro do Couto, P.A., Bustince, H., Melo-Pinto, P. (2010). Automatic histogram threshold using fuzzy measures. IEEE Transactions on Image Processing

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Place Classification using Dempster-Shafer Theory

fields: Extracting the topological structure of indoor environments via place labeling. In In Proc. of the International Joint Conference on Artificial Intelligence (IJCAI , 2007. [9] Harasymowicz-Boggio B., Chechlinski L., and Siemiatkowska B. Nature-inspired, parallel object recognition. In Szewczyk R., Zieliski C., and Kaliczyska M., editors, Progress in Automation, Robotics and Measuring Techniques. Control and Automation. Advances in Intelligent Systems and Computing vol. 350 , pages 53–62. Springer, 2015. [10] Harasymowicz-Boggio B., Chechlinski L

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Modreg: A Modular Framework for RGB-D Image Acquisition and 3D Object Model Registration

K., and Wietrzykowski J. Lightweight RGB-D SLAM System for Search and Rescue Robots. In Progress in Automation, Robotics and Measuring Techniques , pages 11–21. Springer, 2015. [4] Besl P. and McKay N. A method for registration of 3-D shapes. IEEE Transactions on Pattern Analysis and Machine Intelligence , 14(2):239 –256, 1992. [5] Bradski G. and Kaehler A. Learning OpenCV: Computer vision with the OpenCV library . O’Reilly Media, 2008. [6] Correll N., Bekris K. E., Berenson D., Brock O., Causo A., Hauser K., Okada K., Rodriguez A., Romano J

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A note on the differences between Drucker-Prager and Mohr-Coulomb shear strength criteria

equivalent measure of principal stress ratio. Introducing equations (8) - (10) into the definitions of invariants the following relations are obtained: I 1 = 3 p − a q , $${{I}_{1}}=3p-aq,$$ (12) J 2 = q 2 3 ( a 2 + 3 ) , $${{J}_{2}}=\frac{{{q}^{2}}}{3}\left( {{a}^{2}}+3 \right),$$ (13) J 3 = 2 a 27 q 3 ( − a 3 + 9 ) . $$ {{J}_{3}}=\frac{2a}{27}{{q}^{3}}\left( -{{a}^{3}}+9 \right).$$ (14) Finally the Lode angle θ ϵ 〈-π/6, π/6〉 is introduced by

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A Positioning Lockholes of Container Corner Castings Method Based on Image Recognition

Radio-Based Localization of Shipping Containers in the Presence of Incomplete Proximity Information”, IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, Vol. 13, No. 3, pp. 1404- 1419 (2012) 14. Wu Wei, Liu Zheng, Chen Mo, “A New Framework for Container Code Recognition by Using Segmentation- Based and HMM-Based Approaches”, INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE, Vol. 29, No. 1, 2015 15. Yamashita Yukihiko, Wakahara Toru, “Affinetransformation and 2D-projection invariant k-NN classification of

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Statistical Testing of Segment Homogeneity in Classification of Piecewise–Regular Objects

: Multilayer perceptrons vs. dynamic time warping, Neural Networks 3 (4): 453–465. Ciresan, D., Meier, U., Masci, J. and Schmidhuber, J. (2012). Multi-column deep neural network for traffic sign classification, Neural Networks 32 : 333–338. Dalal, N. and Triggs, B. (2005). Histograms of oriented gradients for human detection, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2005, San Diego, CA, USA , pp. 886–893. Gray, R., Buzo, A., Gray, A., Jr. and Matsuyama, Y. (1980). Distortion measures for speech processing

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Some thoughts on bioimpedance and biodielectrics

From early on we learnt that a dielectric is an insulator, and a practical way to measure it was to place it between two capacitor plates. The plates were dry and so was the dielectric – the resistance between the plates was very high. With living tissue it was quite different, the material was not dry and the capacitor plates had wet contact with the tissue. At the wet plates polarization impedance appeared constituting an important source of error. The discipline of bioimpedance had one problem more than the discipline of dielectrics. Even so it became more

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FPGA Implementation of Multi-scale Face Detection Using HOG Features and SVM Classifier

.T., Ogunbona, P., Li, W. (2011). Human detection with contour-based local motion binary patterns. In Image Processing (ICIP), 2011 18th IEEE International Conference on , pp. 3609–3612 [16] Ojala, T., Pietikainen, M., Maenpaa, T. (2002). Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. Pattern Analysis and Machine Intelligence, IEEE Transactions on , 24(7), 971–987 [17] Ojala, T., Pietikainen, M., Harwood, D. (1996). A comparative study of texture measures with classification based on featured distributions

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The steady-state impedance operator of a linear periodically time-varying one-port network and its determination

References Bittanti, S. and Colaneri, P. (1999). Periodic Control. John Wiley Encyclopedia of Electrical and Electronic Engineering , Wiley, New York, NY. Bittanti, S. and Colaneri, P. (2000). Invariant representations of discrete-time periodic systems, Automatica   36 (12): 1777-1793. Bru, R., Romero, S. and Sanchez, E. (2004). Structural properties of positive periodic discrete-time linear systems: Canonical forms, Applied Mathematics and Computation   153 (3): 697

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PLC-Based Pressure Control in Multi-Pump Applications

. on Power Electronics and Applications , EPE 2014-ECCE Europe, Lappeenranta, Finland, 2014 pp. 1–11. [7] P. Xiaohong, X. Laisheng, M. Zhi and L. Guodong, “The variable frequency and speed regulation constant pressure water supply system based on PLC and fuzzy control,” in Int. Conf. on Measuring Technology and Mechatronics Automation, ICMTMA 2009, Zhangjiajie, Hunan, 2009, pp. 910–913. [8] C. Wei1, X. Meixiang and F. Kangling, “A PLC-based fuzzy PID controller for

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