Authors | L. Diachenko1, E. Minov1, S. Ostapov1, P. Fochuk1 , Yu. Khalavka1, A. Bolotnikov2, R.B. James2 |
Affiliations | 1 Chernivtsi National University, Chernivtsi, Ukraine 2 Brookhaven National Laboratory, Upton, New York, USA |
Е-mail | |
Issue | Volume 8, Year 2016, Number 4 |
Dates | Received 15 September 2016; published online 23 December 2016 |
Citation | L. Diachenko, E. Minov, S. Ostapov, et al., J. Nano- Electron. Phys. 8 No 4(2), 04060 (2016) |
DOI | 10.21272/jnep.8(4(2)).04060 |
PACS Number(s) | 07.05.Rm; 07.05.Tp |
Keywords | Optical defect recognition, Nano-tracking analysis, Computer vision, Growth defects, Software developing. |
Annotation | In this paper it is describe a new approach developed for recognizing micro- and nano-sized objects and a method for quantitative analysis of these objects. For this purpose was developed the automated systems that can simplify and accelerate the process of nanoparticle tracks analysis under the microscope whereby engineers and scientists are able to recognize the structures of defects in semiconductor wafers, along with nanoparticles and other microscopic objects. This capability is important to both select appropriate crystals and also to apply the data to improve the production process. |
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