Deep Semi-Supervised Image Classification Algorithms: a Survey
Semi-supervised learning is a branch of machine learning focused on improving the performance of models when the labeled data is scarce, but there is access to large number of unlabeled examples. Over the past five years there has been a remarkable progress in designing algorithms which are able to...
Main Authors: | Ani Vanyan, Hrant Khachatrian |
---|---|
Format: | Article |
Language: | English |
Published: |
Graz University of Technology
2021-12-01
|
Series: | Journal of Universal Computer Science |
Subjects: | |
Online Access: | https://lib.jucs.org/article/77029/download/pdf/ |
Similar Items
-
CLASSIFICATION BASED ON SEMI-SUPERVISED LEARNING: A REVIEW
by: Aska Ezadeen Mehyadin, et al.
Published: (2021-05-01) -
Survey of Multi-label Classification Based on Supervised and Semi-supervised Learning
by: WU Hong-xin, HAN Meng, CHEN Zhi-qiang, ZHANG Xi-long, LI Mu-hang
Published: (2022-08-01) -
Semi-Supervised Learning for Ill-Posed Polarimetric SAR Classification
by: Stefan Uhlmann, et al.
Published: (2014-05-01) -
Self-Supervised Assisted Semi-Supervised Residual Network for Hyperspectral Image Classification
by: Liangliang Song, et al.
Published: (2022-06-01) -
Review of Semi-supervised Deep Learning Image Classification Methods
by: LYU Haoyuan+, YU Lu, ZHOU Xingyu, DENG Xiang
Published: (2021-06-01)