Brain inspired lifelong learning model based on neural based learning classifier system for underwater data classification
作者：
Highlights：
• Lifelong learning with knowledge extraction, retention and reuse capability.
• Exploitation of various CNN blocks for feature extraction.
• Model capable to cover both new instances and new classes scenarios.
• Investigation of multiple learning techniques.
• Better classification accuracy results as compared to deep CNN methods.
摘要
•Lifelong learning with knowledge extraction, retention and reuse capability.•Exploitation of various CNN blocks for feature extraction.•Model capable to cover both new instances and new classes scenarios.•Investigation of multiple learning techniques.•Better classification accuracy results as compared to deep CNN methods.
论文关键词：Lifelong learning,Underwater image classification,Learning classifier systems,Convolutional neural network
论文评审过程：Received 1 February 2021, Revised 14 June 2021, Accepted 23 August 2021, Available online 1 September 2021, Version of Record 8 September 2021.
论文官网地址：https://doi.org/10.1016/j.eswa.2021.115798
