Human-in-the-loop: Using classifier decision boundary maps to improve pseudo labels
-
Published:2024-11
Issue:
Volume:124
Page:104062
-
ISSN:0097-8493
-
Container-title:Computers & Graphics
-
language:en
-
Short-container-title:Computers & Graphics
Author:
Benato Bárbara C.ORCID,
Grosu Cristian,
Falcão Alexandre X.,
Telea Alexandru C.
Funder
FAPESP
CNPq
USP CEPID-CeMEAI
CAPES
Reference61 articles.
1. Lin TY, Maire M, Belongie S, Hays J, Perona P, Ramanan D, et al. Microsoft COCO: Common Objects in Context. In: Proc. ECCV. 2014, p. 740–55.
2. Sun C, Shrivastava A, Singh S, Gupta A. Revisiting Unreasonable Effectiveness of Data in Deep Learning Era. In: Proc. ICCV. 2017, p. 843–52.
3. Generalizing from a few examples: A survey on few-shot learning;Wang;ACM Comput Surv,2020
4. Lee DH. Pseudo-Label : The Simple and Efficient Semi-Supervised Learning Method for Deep Neural Networks. In: Proc. ICML-WREPL. 2013.
5. Iscen A, Tolias G, Avrithis Y, Chum O. Label propagation for deep semi-supervised learning. In: Proc. ICCV. 2019, p. 5070–9.