Semi-Supervised Learning for Fine-Grained Classification With Self-Training

Semi-supervised learning is a machine learning approach that tackles the challenge of having a large set of unlabeled data and few labeled ones. In this paper we adopt a semi-supervised self-training method to increase the amount of training data, prevent overfitting and improve the performance of d...

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Bibliographic Details
Main Authors: Obed Tettey Nartey, Guowu Yang, Jinzhao Wu, Sarpong Kwadwo Asare
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/8943213/