Domain Adaptation Based on Human Feedback for Enhancing Image Denoising in Generative Models
How can human feedback be effectively integrated into generative models? This study addresses this question by proposing a method to enhance image denoising and achieve domain adaptation using human feedback. Deep generative models, while achieving remarkable performance in image denoising within tr...
Saved in:
| Main Authors: | Hyun-Cheol Park, Dat Ngo, Sung Ho Kang |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-02-01
|
| Series: | Mathematics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2227-7390/13/4/598 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Pest detection in dynamic environments: an adaptive continual test-time domain adaptation strategy
by: Rui Fu, et al.
Published: (2025-04-01) -
Adversarial Multitask Learning for Domain Adaptation Through Domain Adapter
by: Hidayaturrahman, et al.
Published: (2024-01-01) -
Study on domain adaptation of medical data based on generative adversarial network
by: Hufei YU, et al.
Published: (2020-09-01) -
Toward Enhanced Adversarial Robustness Generalization in Object Detection: Feature Disentangled Domain Adaptation for Adversarial Training
by: Yoojin Jung, et al.
Published: (2024-01-01) -
GAN-based unsupervised domain adaptive person re-identification
by: Shengsheng ZHENG, et al.
Published: (2021-02-01)