Semi-Supervised Medical Image Classification Combined with Unsupervised Deep Clustering
An effective way to improve the performance of deep neural networks in most computer vision tasks is to improve the quantity of labeled data and the quality of labels. However, in the analysis and processing of medical images, high-quality annotation depends on the experience and professional knowle...
Main Authors: | Lu, C. (Author), Xiao, B. (Author) |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI
2023
|
Subjects: | |
Online Access: | View Fulltext in Publisher View in Scopus |
Similar Items
-
A Survey on Semi-, Self- and Unsupervised Learning for Image Classification
by: Lars Schmarje, et al.
Published: (2021-01-01) -
Semi-Supervised Learning With Deep Embedded Clustering for Image Classification and Segmentation
by: Joseph Enguehard, et al.
Published: (2019-01-01) -
Contributions to Unsupervised and Semi-Supervised Learning
by: Pal, David
Published: (2009) -
Contributions to Unsupervised and Semi-Supervised Learning
by: Pal, David
Published: (2009) -
Integrating Deep Supervised, Self-Supervised and Unsupervised Learning for Single-Cell RNA-seq Clustering and Annotation
by: Liang Chen, et al.
Published: (2020-07-01)