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

• Main Authors: Abubakar, Adamu, Ya’u Gital, Abdulsalam, Chiroma, Haruna, Rana, Nadim, Abdulhamid, Shafi’i, Muhammad, Amina Nuhu, Umar, Aishatu Yahaya
• 格式: Conference or Workshop Item
• 语言: English; English
• 出版: Springer Nature 2019
• 主题: Q350 Information theory
• 在线阅读: http://irep.iium.edu.my/74259/13/74259_Nature%20inspired%20meta-heuristic%20algorithms.pdf; http://irep.iium.edu.my/74259/7/74259_%20nature%20inspired%20meta-heuristic_Scopus.pdf; http://irep.iium.edu.my/74259/; 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

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...