TY - JOUR
T1 - Semi-supervised deep rule-based approach for image classification
AU - Gu, Xiaowei
AU - Angelov, Plamen Parvanov
N1 - Publisher Copyright:
Copyright 2018 Elsevier B.V., All rights reserved.
PY - 2018/7/30
Y1 - 2018/7/30
N2 - In this paper, a semi-supervised learning approach based on a deep rule-based (DRB) classifier is introduced. With its unique prototype-based nature, the semi-supervised DRB (SSDRB) classifier is able to generate human interpretable IF...THEN...rules through the semi-supervised learning process in a self-organising and highly transparent manner. It supports online learning on a sample-by-sample basis or on a chunk-by-chunk basis. It is also able to perform classification on out-of-sample images. Moreover, the SSDRB classifier can learn new classes from unlabelled images in an active way becoming dynamically self-evolving. Numerical examples based on large-scale benchmark image sets demonstrate the strong performance of the proposed SSDRB classifier as well as its distinctive features compared with the “state-of-the-art” approaches.
AB - In this paper, a semi-supervised learning approach based on a deep rule-based (DRB) classifier is introduced. With its unique prototype-based nature, the semi-supervised DRB (SSDRB) classifier is able to generate human interpretable IF...THEN...rules through the semi-supervised learning process in a self-organising and highly transparent manner. It supports online learning on a sample-by-sample basis or on a chunk-by-chunk basis. It is also able to perform classification on out-of-sample images. Moreover, the SSDRB classifier can learn new classes from unlabelled images in an active way becoming dynamically self-evolving. Numerical examples based on large-scale benchmark image sets demonstrate the strong performance of the proposed SSDRB classifier as well as its distinctive features compared with the “state-of-the-art” approaches.
KW - Deep rule-based (DRB) classifier
KW - Fuzzy rules
KW - Prototype-based models
KW - Self-organising classifier
KW - Semi-supervised learning
KW - Transparency and interpretability
UR - http://www.research.lancs.ac.uk/portal/en/publications/semisupervised-deep-rulebased-approach-for-image-classification(9ad0d6f4-79f4-405e-8a3a-db62caf7b126).html
UR - http://www.scopus.com/inward/record.url?scp=85044929335&partnerID=8YFLogxK
U2 - 10.1016/j.asoc.2018.03.032
DO - 10.1016/j.asoc.2018.03.032
M3 - Article
SN - 1568-4946
VL - 68
SP - 53
EP - 68
JO - Applied Soft Computing
JF - Applied Soft Computing
ER -