Benchmarking the Influence of Pre-training on Explanation Performance in MR Image Classification
Fuente:
arXiv
Saved in:
| Main Authors: | Oliveira, Marta, Wilming, Rick, Clark, Benedict, Budding, Céline, Eitel, Fabian, Ritter, Kerstin, Haufe, Stefan |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
GECOBench: A Gender-Controlled Text Dataset and Benchmark for Quantifying Biases in Explanations
by: Wilming, Rick, et al.
Published: (2024)
by: Wilming, Rick, et al.
Published: (2024)
Feature salience - not task-informativeness - drives machine learning model explanations
by: Clark, Benedict, et al.
Published: (2026)
by: Clark, Benedict, et al.
Published: (2026)
The effect of whitening on explanation performance
by: Clark, Benedict, et al.
Published: (2026)
by: Clark, Benedict, et al.
Published: (2026)
A Closer Look at Benchmarking Self-Supervised Pre-training with Image Classification
by: Marks, Markus, et al.
Published: (2024)
by: Marks, Markus, et al.
Published: (2024)
Comparative Performance of Finetuned ImageNet Pre-trained Models for Electronic Component Classification
by: Shao, Yidi, et al.
Published: (2025)
by: Shao, Yidi, et al.
Published: (2025)
Explainable AI needs formalization
by: Haufe, Stefan, et al.
Published: (2024)
by: Haufe, Stefan, et al.
Published: (2024)
Explainable AI Methods for Neuroimaging: Systematic Failures of Common Tools, the Need for Domain-Specific Validation, and a Proposal for Safe Application
by: Siegel, Nys Tjade, et al.
Published: (2025)
by: Siegel, Nys Tjade, et al.
Published: (2025)
Universal Image Restoration Pre-training via Degradation Classification
by: Hu, JiaKui, et al.
Published: (2025)
by: Hu, JiaKui, et al.
Published: (2025)
TIP: Tabular-Image Pre-training for Multimodal Classification with Incomplete Data
by: Du, Siyi, et al.
Published: (2024)
by: Du, Siyi, et al.
Published: (2024)
Universal Image Restoration Pre-training via Masked Degradation Classification
by: Hu, JiaKui, et al.
Published: (2025)
by: Hu, JiaKui, et al.
Published: (2025)
DocVCE: Diffusion-based Visual Counterfactual Explanations for Document Image Classification
by: Saifullah, Saifullah, et al.
Published: (2025)
by: Saifullah, Saifullah, et al.
Published: (2025)
Bayesian Exploration of Pre-trained Models for Low-shot Image Classification
by: Miao, Yibo, et al.
Published: (2024)
by: Miao, Yibo, et al.
Published: (2024)
Multimodal Medical Image Classification via Synergistic Learning Pre-training
by: Lin, Qinghua, et al.
Published: (2025)
by: Lin, Qinghua, et al.
Published: (2025)
Explanations of Classifiers Enhance Medical Image Segmentation via End-to-end Pre-training
by: Chen, Jiamin, et al.
Published: (2024)
by: Chen, Jiamin, et al.
Published: (2024)
RAW-Adapter: Adapting Pre-trained Visual Model to Camera RAW Images and A Benchmark
by: Cui, Ziteng, et al.
Published: (2025)
by: Cui, Ziteng, et al.
Published: (2025)
Synthetic Data Augmentation using Pre-trained Diffusion Models for Long-tailed Food Image Classification
by: Koh, GaYeon, et al.
Published: (2025)
by: Koh, GaYeon, et al.
Published: (2025)
Should VLMs be Pre-trained with Image Data?
by: Keh, Sedrick, et al.
Published: (2025)
by: Keh, Sedrick, et al.
Published: (2025)
Focus on Texture: Rethinking Pre-training in Masked Autoencoders for Medical Image Classification
by: Madan, Chetan, et al.
Published: (2025)
by: Madan, Chetan, et al.
Published: (2025)
Domain-Specific Pre-training Improves Confidence in Whole Slide Image Classification
by: Chitnis, Soham Rohit, et al.
Published: (2023)
by: Chitnis, Soham Rohit, et al.
Published: (2023)
EPIC: Explanation of Pretrained Image Classification Networks via Prototype
by: Borycki, Piotr, et al.
Published: (2025)
by: Borycki, Piotr, et al.
Published: (2025)
Scalable Pre-training of Large Autoregressive Image Models
by: El-Nouby, Alaaeldin, et al.
Published: (2024)
by: El-Nouby, Alaaeldin, et al.
Published: (2024)
Pre-training Everywhere: Parameter-Efficient Fine-Tuning for Medical Image Analysis via Target Parameter Pre-training
by: Lei, Xingliang, et al.
Published: (2024)
by: Lei, Xingliang, et al.
Published: (2024)
MaskedCLIP: Bridging the Masked and CLIP Space for Semi-Supervised Medical Vision-Language Pre-training
by: Zhu, Lei, et al.
Published: (2025)
by: Zhu, Lei, et al.
Published: (2025)
OpenPath: Open-Set Active Learning for Pathology Image Classification via Pre-trained Vision-Language Models
by: Zhong, Lanfeng, et al.
Published: (2025)
by: Zhong, Lanfeng, et al.
Published: (2025)
Pseudo-Prompt Generating in Pre-trained Vision-Language Models for Multi-Label Medical Image Classification
by: Ye, Yaoqin, et al.
Published: (2024)
by: Ye, Yaoqin, et al.
Published: (2024)
Domain-Adaptive Pre-training of Self-Supervised Foundation Models for Medical Image Classification in Gastrointestinal Endoscopy
by: Roth, Marcel, et al.
Published: (2024)
by: Roth, Marcel, et al.
Published: (2024)
Generic Knowledge Boosted Pre-training For Remote Sensing Images
by: Huang, Ziyue, et al.
Published: (2024)
by: Huang, Ziyue, et al.
Published: (2024)
PLIP: Language-Image Pre-training for Person Representation Learning
by: Zuo, Jialong, et al.
Published: (2023)
by: Zuo, Jialong, et al.
Published: (2023)
DreamLIP: Language-Image Pre-training with Long Captions
by: Zheng, Kecheng, et al.
Published: (2024)
by: Zheng, Kecheng, et al.
Published: (2024)
Let ViT Speak: Generative Language-Image Pre-training
by: Fang, Yan, et al.
Published: (2026)
by: Fang, Yan, et al.
Published: (2026)
Sufficient, Necessary and Complete Causal Explanations in Image Classification
by: Kelly, David A, et al.
Published: (2025)
by: Kelly, David A, et al.
Published: (2025)
Why Does It Look There? Structured Explanations for Image Classification
by: Li, Jiarui, et al.
Published: (2026)
by: Li, Jiarui, et al.
Published: (2026)
Towards Scalable Language-Image Pre-training for 3D Medical Imaging
by: Zhao, Chenhui, et al.
Published: (2025)
by: Zhao, Chenhui, et al.
Published: (2025)
Reinforcing Pre-trained Models Using Counterfactual Images
by: Li, Xiang, et al.
Published: (2024)
by: Li, Xiang, et al.
Published: (2024)
What Do Large Language Models Know? Tacit Knowledge as a Potential Causal-Explanatory Structure
by: Budding, Céline
Published: (2025)
by: Budding, Céline
Published: (2025)
Atlas-Based Interpretable Age Prediction In Whole-Body MR Images
by: Starck, Sophie, et al.
Published: (2023)
by: Starck, Sophie, et al.
Published: (2023)
Boosting Image Restoration via Priors from Pre-trained Models
by: Xu, Xiaogang, et al.
Published: (2024)
by: Xu, Xiaogang, et al.
Published: (2024)
Advancing Myopia To Holism: Fully Contrastive Language-Image Pre-training
by: Wang, Haicheng, et al.
Published: (2024)
by: Wang, Haicheng, et al.
Published: (2024)
A Closer Look at the Explainability of Contrastive Language-Image Pre-training
by: Li, Yi, et al.
Published: (2023)
by: Li, Yi, et al.
Published: (2023)
Pre-trained Models Succeed in Medical Imaging with Representation Similarity Degradation
by: Zu, Wenqiang, et al.
Published: (2025)
by: Zu, Wenqiang, et al.
Published: (2025)
Similar Items
-
GECOBench: A Gender-Controlled Text Dataset and Benchmark for Quantifying Biases in Explanations
by: Wilming, Rick, et al.
Published: (2024) -
Feature salience - not task-informativeness - drives machine learning model explanations
by: Clark, Benedict, et al.
Published: (2026) -
The effect of whitening on explanation performance
by: Clark, Benedict, et al.
Published: (2026) -
A Closer Look at Benchmarking Self-Supervised Pre-training with Image Classification
by: Marks, Markus, et al.
Published: (2024) -
Comparative Performance of Finetuned ImageNet Pre-trained Models for Electronic Component Classification
by: Shao, Yidi, et al.
Published: (2025)