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Detection of Nano Particles in TEM Images Using an Ensemble Learning Algorithm

Lohiya, Paranjith Singh

Abstract Details

2015, Master of Computing and Information Systems, Youngstown State University, Department of Computer Science and Information Systems.
Transmission electron microscopy (TEM) has an ability to depict material structures on nanoscales (~0.1 nm). High resolution TEM has found applications in a wide range of domains such as the studies of biological tissues, reactive chemical compounds and product defect inspection. For the past decade, Nano-research has generated a large number of TEM images, each containing immense amount of information that cannot be processed and interpreted manually. The combination of image processing and big data mining becomes the only viable solution. This thesis investigates the feasibility of using a Cascade AdaBoost algorithm to detect and count nanoparticles automatically. Experiments with cube-shaped objects have yielded very promising results with high detection rate (true positive rate) and low false alarm rate (false positive rate). The impacts of labeling variation, sample size and feature size on the detection accuracy were also discussed.
Yong Zhang, PhD (Advisor)
Feng George Yu, PhD (Advisor)
John Sullins, PhD (Committee Member)
38 p.

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Citations

  • Lohiya, P. S. (2015). Detection of Nano Particles in TEM Images Using an Ensemble Learning Algorithm [Master's thesis, Youngstown State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ysu1432915612

    APA Style (7th edition)

  • Lohiya, Paranjith Singh. Detection of Nano Particles in TEM Images Using an Ensemble Learning Algorithm. 2015. Youngstown State University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ysu1432915612.

    MLA Style (8th edition)

  • Lohiya, Paranjith Singh. "Detection of Nano Particles in TEM Images Using an Ensemble Learning Algorithm." Master's thesis, Youngstown State University, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=ysu1432915612

    Chicago Manual of Style (17th edition)