304 related articles for article (PubMed ID: 27627768)
1. Semi-Supervised Active Learning for Sound Classification in Hybrid Learning Environments.
Han W; Coutinho E; Ruan H; Li H; Schuller B; Yu X; Zhu X
PLoS One; 2016; 11(9):e0162075. PubMed ID: 27627768
[TBL] [Abstract][Full Text] [Related]
2. A semi-supervised machine learning framework for microRNA classification.
Sheikh Hassani M; Green JR
Hum Genomics; 2019 Oct; 13(Suppl 1):43. PubMed ID: 31639051
[TBL] [Abstract][Full Text] [Related]
3. Comprehensive study of semi-supervised learning for DNA methylation-based supervised classification of central nervous system tumors.
Tran QT; Alom MZ; Orr BA
BMC Bioinformatics; 2022 Jun; 23(1):223. PubMed ID: 35676649
[TBL] [Abstract][Full Text] [Related]
4. Semi-supervised classifier guided by discriminator.
Jamroziński S; Markowska-Kaczmar U
Sci Rep; 2022 Aug; 12(1):14665. PubMed ID: 36038620
[TBL] [Abstract][Full Text] [Related]
5. A Generic Semi-Supervised and Active Learning Framework for Biomedical Text Classification.
Flores CA; Verschae R
Annu Int Conf IEEE Eng Med Biol Soc; 2022 Jul; 2022():4445-4448. PubMed ID: 36085799
[TBL] [Abstract][Full Text] [Related]
6. Active learning for bird sound classification via a kernel-based extreme learning machine.
Qian K; Zhang Z; Baird A; Schuller B
J Acoust Soc Am; 2017 Oct; 142(4):1796. PubMed ID: 29092546
[TBL] [Abstract][Full Text] [Related]
7. Maximum margin semi-supervised learning with irrelevant data.
Yang H; Huang K; King I; Lyu MR
Neural Netw; 2015 Oct; 70():90-102. PubMed ID: 26264172
[TBL] [Abstract][Full Text] [Related]
8. An empirical study of ensemble-based semi-supervised learning approaches for imbalanced splice site datasets.
Stanescu A; Caragea D
BMC Syst Biol; 2015; 9 Suppl 5(Suppl 5):S1. PubMed ID: 26356316
[TBL] [Abstract][Full Text] [Related]
9. A semi-supervised classification RBM with an improved fMRI representation algorithm.
Chang C; Liu N; Yao L; Zhao X
Comput Methods Programs Biomed; 2022 Jul; 222():106960. PubMed ID: 35753106
[TBL] [Abstract][Full Text] [Related]
10. Supervised threshold-based heart sound classification algorithm.
Han W; Yang Z; Lu J; Xie S
Physiol Meas; 2018 Nov; 39(11):115011. PubMed ID: 30500785
[TBL] [Abstract][Full Text] [Related]
11. Active learning based segmentation of Crohns disease from abdominal MRI.
Mahapatra D; Vos FM; Buhmann JM
Comput Methods Programs Biomed; 2016 May; 128():75-85. PubMed ID: 27040833
[TBL] [Abstract][Full Text] [Related]
12. Feasibility of Active Machine Learning for Multiclass Compound Classification.
Lang T; Flachsenberg F; von Luxburg U; Rarey M
J Chem Inf Model; 2016 Jan; 56(1):12-20. PubMed ID: 26740007
[TBL] [Abstract][Full Text] [Related]
13. Robust Semi-Supervised Traffic Sign Recognition via Self-Training and Weakly-Supervised Learning.
Nartey OT; Yang G; Asare SK; Wu J; Frempong LN
Sensors (Basel); 2020 May; 20(9):. PubMed ID: 32397197
[TBL] [Abstract][Full Text] [Related]
14. A Generic Human-Machine Annotation Framework Based on Dynamic Cooperative Learning.
Zhang Y; Michi A; Wagner J; Andre E; Schuller B; Weninger F
IEEE Trans Cybern; 2020 Mar; 50(3):1230-1239. PubMed ID: 30872254
[TBL] [Abstract][Full Text] [Related]
15. Clinical Document Classification Using Labeled and Unlabeled Data Across Hospitals.
Hassanzadeh H; Kholghi M; Nguyen A; Chu K
AMIA Annu Symp Proc; 2018; 2018():545-554. PubMed ID: 30815095
[TBL] [Abstract][Full Text] [Related]
16. Study on Human Activity Recognition Using Semi-Supervised Active Transfer Learning.
Oh S; Ashiquzzaman A; Lee D; Kim Y; Kim J
Sensors (Basel); 2021 Apr; 21(8):. PubMed ID: 33919823
[TBL] [Abstract][Full Text] [Related]
17. Exploiting the potential of unlabeled endoscopic video data with self-supervised learning.
Ross T; Zimmerer D; Vemuri A; Isensee F; Wiesenfarth M; Bodenstedt S; Both F; Kessler P; Wagner M; Müller B; Kenngott H; Speidel S; Kopp-Schneider A; Maier-Hein K; Maier-Hein L
Int J Comput Assist Radiol Surg; 2018 Jun; 13(6):925-933. PubMed ID: 29704196
[TBL] [Abstract][Full Text] [Related]
18. A Semi-Automatic Annotation Approach for Human Activity Recognition.
Bota P; Silva J; Folgado D; Gamboa H
Sensors (Basel); 2019 Jan; 19(3):. PubMed ID: 30691040
[TBL] [Abstract][Full Text] [Related]
19. A novel logistic regression model combining semi-supervised learning and active learning for disease classification.
Chai H; Liang Y; Wang S; Shen HW
Sci Rep; 2018 Aug; 8(1):13009. PubMed ID: 30158596
[TBL] [Abstract][Full Text] [Related]
20. Improving the Classification Performance of Esophageal Disease on Small Dataset by Semi-supervised Efficient Contrastive Learning.
Du W; Rao N; Yong J; Wang Y; Hu D; Gan T; Zhu L; Zeng B
J Med Syst; 2021 Nov; 46(1):4. PubMed ID: 34807297
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
