INTELLIGENT QUANTITY EXTRACTION FROM A CONTINUOUS MULTIMEDIA STREAM
DOI:
https://doi.org/10.24867/12BE11SlijepcevicKeywords:
Quantity extraction, Digit recognition, Digital image, Machine learning, Neural networksAbstract
This paper describes the problem of intelligent quantity extraction and recognition of handwritten digits from a multimedia stream, as well as a solution to the described problem. The problem was solved with the help of artificial intelligence, machine learning, neural networks and various image processing methods. The software solution to this problem is written in the Python programming language using the associated libraries.
References
[1] Gurney K., „An introduction to neural networks“, University of Sheffield, London and New York, 1997.
[2] Matthew D Zeiler, Rob Fergus, „Visualizing and understanding convolutional networks“, 2013, New York.
[3] R. C. Gonzalez, R. E. Woods, „Digital Image Processing“, Prentice Hall, 2008.
[4] Yuan Yu, Xiaoqiang Zheng. „Large-scale machine learning on heterogeneous systems“, 2015.
[5] http://yann.lecun.com/exdb/mnist/ (pristupljeno u oktobru 2020.)
[2] Matthew D Zeiler, Rob Fergus, „Visualizing and understanding convolutional networks“, 2013, New York.
[3] R. C. Gonzalez, R. E. Woods, „Digital Image Processing“, Prentice Hall, 2008.
[4] Yuan Yu, Xiaoqiang Zheng. „Large-scale machine learning on heterogeneous systems“, 2015.
[5] http://yann.lecun.com/exdb/mnist/ (pristupljeno u oktobru 2020.)
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Published
2021-03-05
Issue
Section
Electrotechnical and Computer Engineering
