Curriculum Fine-tuning of Vision Foundation Model for Medical Image Classification Under Label Noise
Fuente:
arXiv
Saved in:
| Main Authors: | Yu, Yeonguk, Ko, Minhwan, Shin, Sungho, Kim, Kangmin, Lee, Kyoobin |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Adapting Medical Vision Foundation Models for Volumetric Medical Image Segmentation via Active Learning and Selective Semi-supervised Fine-tuning
by: Yang, Jin, et al.
Published: (2025)
by: Yang, Jin, et al.
Published: (2025)
Investigating the Robustness of Vision Transformers against Label Noise in Medical Image Classification
by: Khanal, Bidur, et al.
Published: (2024)
by: Khanal, Bidur, et al.
Published: (2024)
Domain-Specific Block Selection and Paired-View Pseudo-Labeling for Online Test-Time Adaptation
by: Yu, Yeonguk, et al.
Published: (2024)
by: Yu, Yeonguk, et al.
Published: (2024)
Coarse-to-Fine: Progressive Image Compression for Semantically Hierarchical Classification
by: Kim, Jungwoo, et al.
Published: (2026)
by: Kim, Jungwoo, et al.
Published: (2026)
Fine-tuned Generative Adversarial Network-based Model for Medical Image Super-Resolution
by: Aghelan, Alireza, et al.
Published: (2022)
by: Aghelan, Alireza, et al.
Published: (2022)
Subjective and Objective Quality Evaluation of Super-Resolution Enhanced Broadcast Images on a Novel SR-IQA Dataset
by: Kim, Yongrok, et al.
Published: (2024)
by: Kim, Yongrok, et al.
Published: (2024)
Cross-Organ and Cross-Scanner Adenocarcinoma Segmentation using Rein to Fine-tune Vision Foundation Models
by: Cai, Pengzhou, et al.
Published: (2024)
by: Cai, Pengzhou, et al.
Published: (2024)
Vision Foundation Models in Medical Image Analysis: Advances and Challenges
by: Liang, Pengchen, et al.
Published: (2025)
by: Liang, Pengchen, et al.
Published: (2025)
Advancements in Medical Image Classification through Fine-Tuning Natural Domain Foundation Models
by: Mansoori, Mobina, et al.
Published: (2025)
by: Mansoori, Mobina, et al.
Published: (2025)
MedBLIP: Fine-tuning BLIP for Medical Image Captioning
by: Limbu, Manshi, et al.
Published: (2025)
by: Limbu, Manshi, et al.
Published: (2025)
CLOG-CD: Curriculum Learning based on Oscillating Granularity of Class Decomposed Medical Image Classification
by: Abbas, Asmaa, et al.
Published: (2025)
by: Abbas, Asmaa, et al.
Published: (2025)
Pre-trained Under Noise: A Framework for Robust Bone Fracture Detection in Medical Imaging
by: Hoover, Robby, et al.
Published: (2025)
by: Hoover, Robby, et al.
Published: (2025)
Pixels Under Pressure: Exploring Fine-Tuning Paradigms for Foundation Models in High-Resolution Medical Imaging
by: TehraniNasab, Zahra, et al.
Published: (2025)
by: TehraniNasab, Zahra, et al.
Published: (2025)
Adversarial Purification and Fine-tuning for Robust UDC Image Restoration
by: Song, Zhenbo, et al.
Published: (2024)
by: Song, Zhenbo, et al.
Published: (2024)
Fine-tuned Transformer Models for Breast Cancer Detection and Classification
by: Osman, Showkat, et al.
Published: (2025)
by: Osman, Showkat, et al.
Published: (2025)
DIOR-ViT: Differential Ordinal Learning Vision Transformer for Cancer Classification in Pathology Images
by: Lee, Ju Cheon, et al.
Published: (2024)
by: Lee, Ju Cheon, et al.
Published: (2024)
Image Enhancement Based on Pigment Representation
by: Lee, Se-Ho, et al.
Published: (2025)
by: Lee, Se-Ho, et al.
Published: (2025)
Foundation AI Model for Medical Image Segmentation
by: Bao, Rina, et al.
Published: (2024)
by: Bao, Rina, et al.
Published: (2024)
Downstream Analysis of Foundational Medical Vision Models for Disease Progression
by: Demir, Basar, et al.
Published: (2025)
by: Demir, Basar, et al.
Published: (2025)
MedMamba: Vision Mamba for Medical Image Classification
by: Yue, Yubiao, et al.
Published: (2024)
by: Yue, Yubiao, et al.
Published: (2024)
Neighboring Slice Noise2Noise: Self-Supervised Medical Image Denoising from Single Noisy Image Volume
by: Zhou, Langrui, et al.
Published: (2024)
by: Zhou, Langrui, et al.
Published: (2024)
Keyed Nonlinear Transform: Lightweight Privacy-Enhancing Feature Sharing for Medical Image Analysis
by: Lee, Haebom, et al.
Published: (2026)
by: Lee, Haebom, et al.
Published: (2026)
Prompt-driven Latent Domain Generalization for Medical Image Classification
by: Yan, Siyuan, et al.
Published: (2024)
by: Yan, Siyuan, et al.
Published: (2024)
Are Vision Foundation Models Ready for Out-of-the-Box Medical Image Registration?
by: Gu, Hanxue, et al.
Published: (2025)
by: Gu, Hanxue, et al.
Published: (2025)
Pixel Perfect MegaMed: A Megapixel-Scale Vision-Language Foundation Model for Generating High Resolution Medical Images
by: TehraniNasab, Zahra, et al.
Published: (2025)
by: TehraniNasab, Zahra, et al.
Published: (2025)
SemiSAM+: Rethinking Semi-Supervised Medical Image Segmentation in the Era of Foundation Models
by: Zhang, Yichi, et al.
Published: (2025)
by: Zhang, Yichi, et al.
Published: (2025)
Exploring Foundation Models for Synthetic Medical Imaging: A Study on Chest X-Rays and Fine-Tuning Techniques
by: da Silva, Davide Clode, et al.
Published: (2024)
by: da Silva, Davide Clode, et al.
Published: (2024)
MONICA: Benchmarking on Long-tailed Medical Image Classification
by: Ju, Lie, et al.
Published: (2024)
by: Ju, Lie, et al.
Published: (2024)
Label-efficient Single Photon Images Classification via Active Learning
by: Zhang, Zili, et al.
Published: (2025)
by: Zhang, Zili, et al.
Published: (2025)
Enhancing Label-efficient Medical Image Segmentation with Text-guided Diffusion Models
by: Feng, Chun-Mei
Published: (2024)
by: Feng, Chun-Mei
Published: (2024)
Exploring Autoregressive Vision Foundation Models for Image Compression
by: Phung, Huu-Tai, et al.
Published: (2025)
by: Phung, Huu-Tai, et al.
Published: (2025)
Inter-slice Super-resolution of Magnetic Resonance Images by Pre-training and Self-supervised Fine-tuning
by: Wang, Xin, et al.
Published: (2024)
by: Wang, Xin, et al.
Published: (2024)
VM-UNET-V2 Rethinking Vision Mamba UNet for Medical Image Segmentation
by: Zhang, Mingya, et al.
Published: (2024)
by: Zhang, Mingya, et al.
Published: (2024)
A Systematic Review of Generalization Research in Medical Image Classification
by: Matta, Sarah, et al.
Published: (2024)
by: Matta, Sarah, et al.
Published: (2024)
BiasPruner: Debiased Continual Learning for Medical Image Classification
by: Bayasi, Nourhan, et al.
Published: (2024)
by: Bayasi, Nourhan, et al.
Published: (2024)
Aberration Correcting Vision Transformers for High-Fidelity Metalens Imaging
by: Lee, Byeonghyeon, et al.
Published: (2024)
by: Lee, Byeonghyeon, et al.
Published: (2024)
Two-stage Deep Denoising with Self-guided Noise Attention for Multimodal Medical Images
by: Sharif, S M A, et al.
Published: (2025)
by: Sharif, S M A, et al.
Published: (2025)
DiffRect: Latent Diffusion Label Rectification for Semi-supervised Medical Image Segmentation
by: Liu, Xinyu, et al.
Published: (2024)
by: Liu, Xinyu, et al.
Published: (2024)
Selecting the Best Sequential Transfer Path for Medical Image Segmentation with Limited Labeled Data
by: Yang, Jingyun, et al.
Published: (2024)
by: Yang, Jingyun, et al.
Published: (2024)
Med3DVLM: An Efficient Vision-Language Model for 3D Medical Image Analysis
by: Xin, Yu, et al.
Published: (2025)
by: Xin, Yu, et al.
Published: (2025)
Similar Items
-
Adapting Medical Vision Foundation Models for Volumetric Medical Image Segmentation via Active Learning and Selective Semi-supervised Fine-tuning
by: Yang, Jin, et al.
Published: (2025) -
Investigating the Robustness of Vision Transformers against Label Noise in Medical Image Classification
by: Khanal, Bidur, et al.
Published: (2024) -
Domain-Specific Block Selection and Paired-View Pseudo-Labeling for Online Test-Time Adaptation
by: Yu, Yeonguk, et al.
Published: (2024) -
Coarse-to-Fine: Progressive Image Compression for Semantically Hierarchical Classification
by: Kim, Jungwoo, et al.
Published: (2026) -
Fine-tuned Generative Adversarial Network-based Model for Medical Image Super-Resolution
by: Aghelan, Alireza, et al.
Published: (2022)