Nature inspired meta-heuristic algorithms for deep learning: recent progress and novel perspective

Deep learning is presently attracting extra ordinary attention from both the industry and the academia. The application of deep learning in computer vision has recently gain popularity. The optimization of deep learning models through nature inspired algorithms is a subject of debate in computer...

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Main Authors:	Abubakar, Adamu, Ya’u Gital, Abdulsalam, Chiroma, Haruna, Rana, Nadim, Abdulhamid, Shafi’i, Muhammad, Amina Nuhu, Umar, Aishatu Yahaya
Format:	Conference or Workshop Item
Language:	English English
Published:	Springer Nature 2019
Subjects:	Q350 Information theory
Online Access:	http://irep.iium.edu.my/74259/ http://irep.iium.edu.my/74259/ http://irep.iium.edu.my/74259/ http://irep.iium.edu.my/74259/1/Advances%2Bin%2BComputer%2BVision.pdf http://irep.iium.edu.my/74259/7/74259_%20nature%20inspired%20meta-heuristic_Scopus.pdf

id	iium-74259
recordtype	eprints
spelling	iium-742592019-10-24T19:42:01Z http://irep.iium.edu.my/74259/ Nature inspired meta-heuristic algorithms for deep learning: recent progress and novel perspective Abubakar, Adamu Ya’u Gital, Abdulsalam Chiroma, Haruna Rana, Nadim Abdulhamid, Shafi’i Muhammad, Amina Nuhu Umar, Aishatu Yahaya Q350 Information theory Deep learning is presently attracting extra ordinary attention from both the industry and the academia. The application of deep learning in computer vision has recently gain popularity. The optimization of deep learning models through nature inspired algorithms is a subject of debate in computer science. The application areas of the hybrid of natured inspired algorithms and deep learning architecture includes: machine vision and learning, image processing, data science, autonomous vehicles, medical image analysis, biometrics, etc. In this paper, we present recent progress on the application of nature inspired algorithms in deep learning. The survey pointed out recent development issues, strengths, weaknesses and prospects for future research. A new taxonomy is created based on natured inspired algorithms for deep learning. The trend of the publications in this domain is depicted; it shows the research area is growing but slowly. The deep learning architectures not exploit by the nature inspired algorithms for optimization are unveiled. We believed that the survey can facilitate synergy between the nature inspired algorithms and deep learning research communities. As such, massive attention can be expected in a near future. Springer Nature 2019-04-25 Conference or Workshop Item PeerReviewed application/pdf en http://irep.iium.edu.my/74259/1/Advances%2Bin%2BComputer%2BVision.pdf application/pdf en http://irep.iium.edu.my/74259/7/74259_%20nature%20inspired%20meta-heuristic_Scopus.pdf Abubakar, Adamu and Ya’u Gital, Abdulsalam and Chiroma, Haruna and Rana, Nadim and Abdulhamid, Shafi’i and Muhammad, Amina Nuhu and Umar, Aishatu Yahaya (2019) Nature inspired meta-heuristic algorithms for deep learning: recent progress and novel perspective. In: Computer Vision Conference (CVC) 2019, 25-26 April 2019, Las Vegas, Nevada. https://link.springer.com/chapter/10.1007/978-3-030-17795-9_5#citeas https://doi.org/10.1007/978-3-030-17795-9_5
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English English
topic	Q350 Information theory
spellingShingle	Q350 Information theory Abubakar, Adamu Ya’u Gital, Abdulsalam Chiroma, Haruna Rana, Nadim Abdulhamid, Shafi’i Muhammad, Amina Nuhu Umar, Aishatu Yahaya Nature inspired meta-heuristic algorithms for deep learning: recent progress and novel perspective
description	Deep learning is presently attracting extra ordinary attention from both the industry and the academia. The application of deep learning in computer vision has recently gain popularity. The optimization of deep learning models through nature inspired algorithms is a subject of debate in computer science. The application areas of the hybrid of natured inspired algorithms and deep learning architecture includes: machine vision and learning, image processing, data science, autonomous vehicles, medical image analysis, biometrics, etc. In this paper, we present recent progress on the application of nature inspired algorithms in deep learning. The survey pointed out recent development issues, strengths, weaknesses and prospects for future research. A new taxonomy is created based on natured inspired algorithms for deep learning. The trend of the publications in this domain is depicted; it shows the research area is growing but slowly. The deep learning architectures not exploit by the nature inspired algorithms for optimization are unveiled. We believed that the survey can facilitate synergy between the nature inspired algorithms and deep learning research communities. As such, massive attention can be expected in a near future.
format	Conference or Workshop Item
author	Abubakar, Adamu Ya’u Gital, Abdulsalam Chiroma, Haruna Rana, Nadim Abdulhamid, Shafi’i Muhammad, Amina Nuhu Umar, Aishatu Yahaya
author_facet	Abubakar, Adamu Ya’u Gital, Abdulsalam Chiroma, Haruna Rana, Nadim Abdulhamid, Shafi’i Muhammad, Amina Nuhu Umar, Aishatu Yahaya
author_sort	Abubakar, Adamu
title	Nature inspired meta-heuristic algorithms for deep learning: recent progress and novel perspective
title_short	Nature inspired meta-heuristic algorithms for deep learning: recent progress and novel perspective
title_full	Nature inspired meta-heuristic algorithms for deep learning: recent progress and novel perspective
title_fullStr	Nature inspired meta-heuristic algorithms for deep learning: recent progress and novel perspective
title_full_unstemmed	Nature inspired meta-heuristic algorithms for deep learning: recent progress and novel perspective
title_sort	nature inspired meta-heuristic algorithms for deep learning: recent progress and novel perspective
publisher	Springer Nature
publishDate	2019
url	http://irep.iium.edu.my/74259/ http://irep.iium.edu.my/74259/ http://irep.iium.edu.my/74259/ http://irep.iium.edu.my/74259/1/Advances%2Bin%2BComputer%2BVision.pdf http://irep.iium.edu.my/74259/7/74259_%20nature%20inspired%20meta-heuristic_Scopus.pdf
first_indexed	2023-09-18T21:45:11Z
last_indexed	2023-09-18T21:45:11Z
_version_	1777413402385186816

Nature inspired meta-heuristic algorithms for deep learning: recent progress and novel perspective

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