Image de couverture de livre

When Imbalance Comes Twice: Active Learning under Simulated Class Imbalance and Label Shift in Binary Semantic Segmentation

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Combes, Julien, Derville, Alexandre, Coeurjolly, Jean-François
Format:	Preprint
Publié:	2026
Sujets:	Computer Vision and Pattern Recognition
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Instance-wise Uncertainty for Class Imbalance in Semantic Segmentation
par: Almeida, Luís, et autres
Publié: (2024)

Subspace Prototype Guidance for Mitigating Class Imbalance in Point Cloud Semantic Segmentation
par: Han, Jiawei, et autres
Publié: (2024)

Dynamic Label Injection for Imbalanced Industrial Defect Segmentation
par: Caruso, Emanuele, et autres
Publié: (2024)

Class-Imbalanced Semi-Supervised Learning for Large-Scale Point Cloud Semantic Segmentation via Decoupling Optimization
par: Li, Mengtian, et autres
Publié: (2024)

Leveraging Label Proportion Prior for Class-Imbalanced Semi-Supervised Learning
par: Akiba, Kohki, et autres
Publié: (2026)

Defying Imbalanced Forgetting in Class Incremental Learning
par: Xu, Shixiong, et autres
Publié: (2024)

Contrastive Conditional Alignment based on Label Shift Calibration for Imbalanced Domain Adaptation
par: Sun, Xiaona, et autres
Publié: (2024)

Few-Shot Learning with Class Imbalance
par: Ochal, Mateusz, et autres
Publié: (2021)

Revisiting Generative Adversarial Networks for Binary Semantic Segmentation on Imbalanced Datasets
par: Xu, Lei, et autres
Publié: (2024)

Gradient Reweighting: Towards Imbalanced Class-Incremental Learning
par: He, Jiangpeng, et autres
Publié: (2024)

Shape Transformation Driven by Active Contour for Class-Imbalanced Semi-Supervised Medical Image Segmentation
par: Gu, Yuliang, et autres
Publié: (2024)

Class Similarity Transition: Decoupling Class Similarities and Imbalance from Generalized Few-shot Segmentation
par: Wang, Shihong, et autres
Publié: (2024)

A Tale of Two Classes: Adapting Supervised Contrastive Learning to Binary Imbalanced Datasets
par: Mildenberger, David, et autres
Publié: (2025)

Imbalanced Medical Image Segmentation with Pixel-dependent Noisy Labels
par: Guo, Erjian, et autres
Publié: (2025)

Dual-View Alignment Learning with Hierarchical-Prompt for Class-Imbalance Multi-Label Classification
par: Huang, Sheng, et autres
Publié: (2025)

Hyperbolic Active Learning for Semantic Segmentation under Domain Shift
par: Franco, Luca, et autres
Publié: (2023)

Right Regions, Wrong Labels: Semantic Label Flips in Segmentation under Correlation Shift
par: Achara, Akshit, et autres
Publié: (2026)

Leveraging Textual Anatomical Knowledge for Class-Imbalanced Semi-Supervised Multi-Organ Segmentation
par: Gu, Yuliang, et autres
Publié: (2025)

CLIMB-3D: Continual Learning for Imbalanced 3D Instance Segmentation
par: Thengane, Vishal, et autres
Publié: (2025)

CDMAD: Class-Distribution-Mismatch-Aware Debiasing for Class-Imbalanced Semi-Supervised Learning
par: Lee, Hyuck, et autres
Publié: (2024)

Learning Class Difficulty in Imbalanced Histopathology Segmentation via Dynamic Focal Attention
par: Kumari, Lakmali Nadeesha, et autres
Publié: (2026)

Rethinking Class-Incremental Learning from a Dynamic Imbalanced Learning Perspective
par: Wang, Leyuan, et autres
Publié: (2024)

FocalCount: Towards Class-Count Imbalance in Class-Agnostic Counting
par: Zhu, Huilin, et autres
Publié: (2025)

Class-wise Flooding Regularization for Imbalanced Image Classification
par: Aizawa, Hiroaki, et autres
Publié: (2025)

Alleviating Class Imbalance in Semi-supervised Multi-organ Segmentation via Balanced Subclass Regularization
par: Feng, Zhenghao, et autres
Publié: (2024)

Class Uncertainty: A Measure to Mitigate Class Imbalance
par: Baltaci, Z. S., et autres
Publié: (2023)

RICASSO: Reinforced Imbalance Learning with Class-Aware Self-Supervised Outliers Exposure
par: Zhang, Xuan, et autres
Publié: (2024)

Federated Medical Image Classification under Class and Domain Imbalance exploiting Synthetic Sample Generation
par: Pavan, Martina, et autres
Publié: (2026)

Training Class-Imbalanced Diffusion Model Via Overlap Optimization
par: Yan, Divin, et autres
Publié: (2024)

GBRIP: Granular Ball Representation for Imbalanced Partial Label Learning
par: Huang, Jintao, et autres
Publié: (2024)

Addressing Imbalance for Class Incremental Learning in Medical Image Classification
par: Hao, Xuze, et autres
Publié: (2024)

Understanding Imbalanced Forgetting in Rehearsal-Based Class-Incremental Learning
par: Tamajo, Alberto, et autres
Publié: (2026)

Mitigating Background Shift in Class-Incremental Semantic Segmentation
par: Park, Gilhan, et autres
Publié: (2024)

Think Twice Before Selection: Federated Evidential Active Learning for Medical Image Analysis with Domain Shifts
par: Chen, Jiayi, et autres
Publié: (2023)

LCGC: Learning from Consistency Gradient Conflicting for Class-Imbalanced Semi-Supervised Debiasing
par: Xing, Weiwei, et autres
Publié: (2025)

Active Label Refinement for Robust Training of Imbalanced Medical Image Classification Tasks in the Presence of High Label Noise
par: Khanal, Bidur, et autres
Publié: (2024)

CALF: A Conditionally Adaptive Loss Function to Mitigate Class-Imbalanced Segmentation
par: Alam, Bashir, et autres
Publié: (2025)

Pooling Image Datasets With Multiple Covariate Shift and Imbalance
par: Chytas, Sotirios Panagiotis, et autres
Publié: (2024)

Gradient-based Sampling for Class Imbalanced Semi-supervised Object Detection
par: Li, Jiaming, et autres
Publié: (2024)

Boosting with Lexicographic Programming: Addressing Class Imbalance without Cost Tuning
par: Datta, Shounak, et autres
Publié: (2017)