In this essay, the researcher is focusing on the deep learning systems and its major applications in various fields. Song Yukun uses the relu incentive algorithm and the convolution functions to make the program automatically recognize different things or same type of things with different features. Before actually processing the image recognition part, the researcher adds a transforming program which change all kinds of image into one small form. Then, using this modelled image, the program could delicately determine the type of the contents in the image. This technological program is automatic and performs as an essential part of artificial intelligences. The main work it does is imitating the learning process of human brain, which accumulate experiences from thousands of events. It realizes this function by adding different algorithms in the program including the relu incentive algorithm which “teaches” the program particular types of images. After massive input, this technological program could quickly solve current problems with the lack of human labor force doing repetitive but intelligent works like checking particular tumor in the X-ray films. Besides, learning by themselves, the programs could generate results more specific than humans do. This deep-learning principle could be widely utilized since everything in human lives are learning and accumulating experiences. It could change any previous mechanical program into “intelligent” programs which would have an acceleration in their delicacy of determination.
| Published in | American Journal of Computer Science and Technology (Volume 2, Issue 2) |
| DOI | 10.11648/j.ajcst.20190202.11 |
| Page(s) | 22-26 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2019. Published by Science Publishing Group |
Deep Learning, Convolutional Neural Network (CNN), Image Recognition
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APA Style
Song Yukun. (2019). Deep Learning Applications in the Medical Image Recognition. American Journal of Computer Science and Technology, 2(2), 22-26. https://doi.org/10.11648/j.ajcst.20190202.11
ACS Style
Song Yukun. Deep Learning Applications in the Medical Image Recognition. Am. J. Comput. Sci. Technol. 2019, 2(2), 22-26. doi: 10.11648/j.ajcst.20190202.11
AMA Style
Song Yukun. Deep Learning Applications in the Medical Image Recognition. Am J Comput Sci Technol. 2019;2(2):22-26. doi: 10.11648/j.ajcst.20190202.11
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Download@article{10.11648/j.ajcst.20190202.11,
author = {Song Yukun},
title = {Deep Learning Applications in the Medical Image Recognition},
journal = {American Journal of Computer Science and Technology},
volume = {2},
number = {2},
pages = {22-26},
doi = {10.11648/j.ajcst.20190202.11},
url = {https://doi.org/10.11648/j.ajcst.20190202.11},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajcst.20190202.11},
abstract = {In this essay, the researcher is focusing on the deep learning systems and its major applications in various fields. Song Yukun uses the relu incentive algorithm and the convolution functions to make the program automatically recognize different things or same type of things with different features. Before actually processing the image recognition part, the researcher adds a transforming program which change all kinds of image into one small form. Then, using this modelled image, the program could delicately determine the type of the contents in the image. This technological program is automatic and performs as an essential part of artificial intelligences. The main work it does is imitating the learning process of human brain, which accumulate experiences from thousands of events. It realizes this function by adding different algorithms in the program including the relu incentive algorithm which “teaches” the program particular types of images. After massive input, this technological program could quickly solve current problems with the lack of human labor force doing repetitive but intelligent works like checking particular tumor in the X-ray films. Besides, learning by themselves, the programs could generate results more specific than humans do. This deep-learning principle could be widely utilized since everything in human lives are learning and accumulating experiences. It could change any previous mechanical program into “intelligent” programs which would have an acceleration in their delicacy of determination.},
year = {2019}
}
TY - JOUR T1 - Deep Learning Applications in the Medical Image Recognition AU - Song Yukun Y1 - 2019/07/26 PY - 2019 N1 - https://doi.org/10.11648/j.ajcst.20190202.11 DO - 10.11648/j.ajcst.20190202.11 T2 - American Journal of Computer Science and Technology JF - American Journal of Computer Science and Technology JO - American Journal of Computer Science and Technology SP - 22 EP - 26 PB - Science Publishing Group SN - 2640-012X UR - https://doi.org/10.11648/j.ajcst.20190202.11 AB - In this essay, the researcher is focusing on the deep learning systems and its major applications in various fields. Song Yukun uses the relu incentive algorithm and the convolution functions to make the program automatically recognize different things or same type of things with different features. Before actually processing the image recognition part, the researcher adds a transforming program which change all kinds of image into one small form. Then, using this modelled image, the program could delicately determine the type of the contents in the image. This technological program is automatic and performs as an essential part of artificial intelligences. The main work it does is imitating the learning process of human brain, which accumulate experiences from thousands of events. It realizes this function by adding different algorithms in the program including the relu incentive algorithm which “teaches” the program particular types of images. After massive input, this technological program could quickly solve current problems with the lack of human labor force doing repetitive but intelligent works like checking particular tumor in the X-ray films. Besides, learning by themselves, the programs could generate results more specific than humans do. This deep-learning principle could be widely utilized since everything in human lives are learning and accumulating experiences. It could change any previous mechanical program into “intelligent” programs which would have an acceleration in their delicacy of determination. VL - 2 IS - 2 ER -
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