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Deep learning: Applications, architectures, models, tools, and frameworks: A comprehensive survey
,
Fereshteh Ebrahimzadeh,
Mohamadtaghi Rahimi,
Mahdieh Moazzamigodarzi,
Yang Liu ,
Pijush Kanti Dutta Pramanik,
Mohammad Ali Heravi,
Abolfazl Mehbodniya ,
Mustafa Ghaderzadeh ,
Mohammad Reza Feylizadeh,
Saeed Kosari
CAAI Transactions on Intelligence Technology, Volume: 8, Issue: 3, Pages: 581 - 606
Swansea University Author:
Yang Liu
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DOI (Published version): 10.1049/cit2.12180
Abstract
Deep Learning (DL) is a subfield of machine learning that significantly impacts extracting new knowledge. By using DL, the extraction of advanced data representations and knowledge can be made possible. Highly effective DL techniques help to find more hidden knowledge. Deep learning has a promising...
| Published in: | CAAI Transactions on Intelligence Technology |
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| ISSN: | 2468-2322 2468-2322 |
| Published: |
Institution of Engineering and Technology (IET)
2023
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| Online Access: |
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| URI: | https://cronfa.swan.ac.uk/Record/cronfa67387 |
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| Abstract: |
Deep Learning (DL) is a subfield of machine learning that significantly impacts extracting new knowledge. By using DL, the extraction of advanced data representations and knowledge can be made possible. Highly effective DL techniques help to find more hidden knowledge. Deep learning has a promising future due to its great performance and accuracy. We need to understand the fundamentals and the state-of-the-art of DL to leverage it effectively. A survey on DL ways, advantages, drawbacks, architectures, and methods to have a straightforward and clear understanding of it from different views is explained in the paper. Moreover, the existing related methods are compared with each other, and the application of DL is described in some applications, such as medical image analysis, handwriting recognition, and so on. |
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| Keywords: |
data mining; data privacy; deep learning |
| College: |
Faculty of Science and Engineering |
| Issue: |
3 |
| Start Page: |
581 |
| End Page: |
606 |