참고문헌 (44)

1. 10.1007/978-3-642-33905-9 

   

2. Malamas, Elias N, Petrakis, Euripides G.M, Zervakis, Michalis, Petit, Laurent, Legat, Jean-Didier. A survey on industrial vision systems, applications and tools. Image and vision computing, vol.21, no.2, 171-188.

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3. Moganti, Madhav, Ercal, Fikret, Dagli, Cihan H., Tsunekawa, Shou. Automatic PCB Inspection Algorithms: A Survey. Computer vision and image understanding : CVIU, vol.63, no.2, 287-313.

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4. International conference on signal processing applications and technology (ICSPAT’98) Kim KH 

5. International conference on signal processing applications and technology Chung Y 

6. 10.4103/0256-4602.110555 

   

7. Paul, Anand, Bharanitharan, K., Wang, Jhing-Fa. Region similarity based edge detection for motion estimation in H.264/AVC. IEICE Electronics Express, vol.7, no.2, 47-52.

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8. International conference on signal processing applications and technology (ICSPAT’98) Khandogin I 

9. Tretter, Daniel, Bouman, Charles A., Khawaja, Khalid W., Maciejewski, Anthony A.. A multiscale stochastic image model for automated inspection. IEEE transactions on image processing : a publication of the IEEE Signal Processing Society, vol.4, no.12, 1641-1654.

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10. Paul, Anand. Adaptive Search Window for High Efficiency Video Coding. Journal of signal processing systems : for signal, image, and video technology, vol.79, no.3, 257-262.

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11. 10.4103/0256-4602.107336 

    

12. Chen, Shangong, Lin, Bin, Han, Xuesong, Liang, Xiaohu. Automated inspection of engineering ceramic grinding surface damage based on image recognition. International journal of advanced manufacturing technology, vol.66, no.1, 431-443.

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13. Unay, D., Gosselin, B., Kleynen, O., Leemans, V., Destain, M.F., Debeir, O.. Automatic grading of Bi-colored apples by multispectral machine vision. Computers and electronics in agriculture, vol.75, no.1, 204-212.

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14. Yuen, C.W.M., Wong, W.K., Qian, S.Q., Chan, L.K., Fung, E.H.K.. A hybrid model using genetic algorithm and neural network for classifying garment defects. Expert systems with applications, vol.36, no.2, 2037-2047.

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15. 10.4304/jsw.5.6.573-578 

    

16. Dietterich, Thomas G., Lathrop, Richard H., Lozano-Pérez, Tomás. Solving the multiple instance problem with axis-parallel rectangles. Artificial intelligence, vol.89, no.1, 31-71.

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17. 2005 IEEE international conference on multimedia and expo (ICME 2005) Zhang C 1142 

18. Paul, Anand, Rho, Seungmin, Bharnitharan, K.. Interactive scheduling for mobile multimedia service in M2M environment. Multimedia tools and applications, vol.71, no.1, 235-246.

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19. 2009 IEEE conference on computer vision and pattern recognition (CVPR 2009) Babenko B 983 

20. Paul, Anand, Pinjari, Hameed, Hong, Won-Hwa, Seo, Hyun Cheol, Rho, Seungmin. Fog Computing-Based IoT for Health Monitoring System. Journal of sensors, vol.2018, 1-7.

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21. A vision of cyber-physical cloud computing for smart networked systems Simmon E 10.6028/NIST.IR.7951 

    

22. Wang, Yunbo, Vuran, Mehmet C., Goddard, Steve. Cyber-physical systems in industrial process control. SIGBED review, vol.5, no.1, 1-2.

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23. 2nd international conference on applied and theoretical information systems research Zhou J 

24. 2006 IEEE international symposium on industrial electronics Vasilic S 469 

25. ACM T Embed Comput S Paul A 25 12 2 2013 

26. Wu, Jianxin, Bai, Xiang, Loog, Marco, Roli, Fabio, Zhou, Zhi-Hua. Editorial of the Special Issue on Multi-instance Learning in Pattern Recognition and Vision. Pattern recognition, vol.71, 444-445.

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27. Encyclopedia of machine learning Ray S 701 2011 10.1007/978-0-387-30164-8_569 

    

28. Reka, S.S., Ramesh, V.. Demand side management scheme in smart grid with cloud computing approach using stochastic dynamic programming. Perspectives in science, vol.8, 169-171.

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29. Proceedings of the 1st ACM/IEEE international conference on cyber-physical systems Parolini L 168 

30. 2010 9th IEEE/IAS international conference on industry applications (INDUSCON) Zhao P 1 

31. Peng Zhao, Suryanarayanan, S., Simoes, M. G.. An Energy Management System for Building Structures Using a Multi-Agent Decision-Making Control Methodology. IEEE transactions on industry applications, vol.49, no.1, 322-330.

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32. ACM T Embed Comput S Paul A 40 11 2012 

33. Lee, Jay, Bagheri, Behrad, Kao, Hung-An. A Cyber-Physical Systems architecture for Industry 4.0-based manufacturing systems. Manufacturing letters, vol.3, 18-23.

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34. Paul, Anand, Rho, Seungmin. Probabilistic Model for M2M in IoT networking and communication. Telecommunication systems, vol.62, no.1, 59-66.

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35. Proceedings of the 2003 IEEE 46th Midwest symposium on circuits and systems Paul A 

36. Paul, Anand. Real-Time Power Management for Embedded M2M Using Intelligent Learning Methods. ACM transactions on embedded computing systems, vol.13, no.5, 1-22.

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37. Daniel, Alfred, Paul, Anand, Ahmad, Awais, Rho, Seungmin. Cooperative Intelligence of Vehicles for Intelligent Transportation Systems (ITS). Wireless personal communications, vol.87, no.2, 461-484.

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38. Paul, Anand, Daniel, Alfred, Ahmad, Awais, Rho, Seungmin. Cooperative Cognitive Intelligence for Internet of Vehicles. IEEE systems journal, vol.11, no.3, 1249-1258.

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39. Proceeding of the 2013 research in adaptive and convergent systems Paul A 45 

40. Intelligent vehicular networks and communications: fundamentals, architectures and solutions Paul A 2016 

41. Paul, Anand, Ahmad, Awais, Rathore, M. Mazhar, Jabbar, Sohail. Smartbuddy: defining human behaviors using big data analytics in social internet of things. IEEE wireless communications, vol.23, no.5, 68-74.

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42. A comparison of multi-instance learning algorithms Dong L 2006 

43. Cheplygina, V., Tax, D.M.J., Loog, M.. Multiple instance learning with bag dissimilarities. Pattern recognition, vol.48, no.1, 264-275.

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44. MIL: a MATLAB toolbox for multiple instance learning Tax DMJ 2011 

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