Usage of neural networks in image recognition

Authors

DOI:

https://doi.org/10.31617/zt.knute.2019(104)07

Keywords:

neural network, object recognition, classification, domains

Abstract

This article focuses on the operation of the classification of blueprint parts. Classification characteristic is the main part of the designation of the part or product and their design documents, solving a number of topical tasks from creation of a single information language for automated systems to unification and standardization.

Author Biographies

Olena KRYVORUCHKO, Kyiv National University of Trade and Economics

DSc (Engineering), Professor, Head of Department of Software Engineering
and Cyber Security

Karyna KHOROLSKA, Softorino Inc.

Server-side Developer,
Softorino Inc.

Vitalii CHUBAIEVSKYI, Kyiv National University of Trade and Economics

PhD (Political Sciences), Associate Professor of Department of Software Engineering and Cyber Security

References

Alexandre, L. A. (2016). 3D Object Recognition Using Convolutional Neural Networks with Transfer Learning Between Input Channels. In: Menegatti E., Michael N., Berns K., Yamaguchi H. (Eds). Intelligent Autonomous Systems 13. Advances in Intelligent Systems and Computing. (vol. 302). Springer, Cham. DOI: https://doi.org/10.1007/978-3-319-08338-4_64 [in English].

Andre, Esteva, & Brett, Kuprel (2017).Dermatologist-level classification of skin cancer with deep neural networks. (Vol. 542), (pp. 115–118). 02 February. Retrieved from https://www.nature.com/articles/nature21056?TB_iframe=true&width=914.4&height=921.6. DOI: https://doi.org/10.1038/nature21056 [in English].

Popescu, A. C., & Farid, H. (2005). Exposing digital forgeries by detecting traces of resampling. IEEE Transactions on signal processing. (Vol. 53), 2, (pp. 758-767). DOI: https://doi.org/10.1109/TSP.2004.839932 [in English].

Qian, Y., Dong, J., Wang, W., & Tan, T. (2015). Deep learning for steganalysis via convolutional neural networks. Media Watermarking, Security and Forensics. (Vol. 9409), (pp. 94 090J). DOI: https://doi.org/10.1117/12.2083479 [in English].

Lin, M., Chen, Q., & Yan, S. (2014). Network in network, in International Conference on Learning Representations [in English].

Ciresan, D. C., Meier, U. J., Masci, Gambardella L. M., & Schmidhuber J. (2011). High-performance neural networks for visual object classification. Arxiv preprint arXiv:1102.0183 [in English].

Hinton, G. E. (2012). Imagenet classification with deep convolutional neural networks, in Advances in neural information processing systems, (pp. 1097-1105) [in English].

Additional Files

Published

2019-06-19

How to Cite

KRYVORUCHKO, O., KHOROLSKA, K., & CHUBAIEVSKYI, V. (2019). Usage of neural networks in image recognition. oreign rade: onomics, inance, aw, 104(3), 83–101. https://doi.org/10.31617/zt.knute.2019(104)07

Issue

Section

DIGITAL TECHNOLOGIES