Copertina

Multi-Site Class-Incremental Learning with Weighted Experts in Echocardiography

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Bransby, Kit M., Kim, Woo-jin Cho, Oliveira, Jorge, Thorley, Alex, Beqiri, Arian, Gomez, Alberto, Chartsias, Agisilaos
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Computer Vision and Pattern Recognition Artificial Intelligence
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

BackMix: Mitigating Shortcut Learning in Echocardiography with Minimal Supervision
di: Bransby, Kit Mills, et al.
Pubblicazione: (2024)

Uncertainty Propagation for Echocardiography Clinical Metric Estimation via Contour Sampling
di: Judge, Thierry, et al.
Pubblicazione: (2025)

Learning to Stop: Reinforcement Learning for Efficient Patient-Level Echocardiographic Classification
di: Kim, Woo-Jin Cho, et al.
Pubblicazione: (2025)

Fully Automatic Data Labeling for Ultrasound Screen Detection
di: Gomez, Alberto, et al.
Pubblicazione: (2025)

Anatomically Constrained Transformers for Echocardiogram Analysis
di: Thorley, Alexander, et al.
Pubblicazione: (2025)

Efficient Semantic Diffusion Architectures for Model Training on Synthetic Echocardiograms
di: Stojanovski, David, et al.
Pubblicazione: (2024)

FIRE: Unsupervised bi-directional inter-modality registration using deep networks
di: Wang, Chengjia, et al.
Pubblicazione: (2019)

Merge and Bound: Direct Manipulations on Weights for Class Incremental Learning
di: Kim, Taehoon, et al.
Pubblicazione: (2025)

Stable Routing for Mixture-of-Experts in Class-Incremental Learning
di: Guo, Zirui, et al.
Pubblicazione: (2026)

Class-Independent Increment: An Efficient Approach for Multi-label Class-Incremental Learning
di: Ding, Chenhao, et al.
Pubblicazione: (2025)

Joint Dense-Point Representation for Contour-Aware Graph Segmentation
di: Bransby, Kit Mills, et al.
Pubblicazione: (2023)

Adaptive Weighted Parameter Fusion with CLIP for Class-Incremental Learning
di: Guo, Juncen, et al.
Pubblicazione: (2025)

Anatomically Constrained Transformers for Cardiac Amyloidosis Classification
di: Thorley, Alexander, et al.
Pubblicazione: (2025)

Cross-Class Feature Augmentation for Class Incremental Learning
di: Kim, Taehoon, et al.
Pubblicazione: (2023)

Rebalancing Multi-Label Class-Incremental Learning
di: Du, Kaile, et al.
Pubblicazione: (2024)

Tripartite Weight-Space Ensemble for Few-Shot Class-Incremental Learning
di: Lee, Juntae, et al.
Pubblicazione: (2025)

Learn by Reasoning: Analogical Weight Generation for Few-Shot Class-Incremental Learning
di: Han, Jizhou, et al.
Pubblicazione: (2025)

SDDGR: Stable Diffusion-based Deep Generative Replay for Class Incremental Object Detection
di: Kim, Junsu, et al.
Pubblicazione: (2024)

Enhancing Robustness in Incremental Learning with Adversarial Training
di: Cho, Seungju, et al.
Pubblicazione: (2023)

AWF: Adaptive Weight Fusion for Enhanced Class Incremental Semantic Segmentation
di: Sun, Zechao, et al.
Pubblicazione: (2024)

Understanding Imbalanced Forgetting in Rehearsal-Based Class-Incremental Learning
di: Tamajo, Alberto, et al.
Pubblicazione: (2026)

Exemplar-Free Class Incremental Learning via Incremental Representation
di: Huang, Libo, et al.
Pubblicazione: (2024)

DiffClass: Diffusion-Based Class Incremental Learning
di: Meng, Zichong, et al.
Pubblicazione: (2024)

Class Balance Matters to Active Class-Incremental Learning
di: Huang, Zitong, et al.
Pubblicazione: (2024)

Confidence Self-Calibration for Multi-Label Class-Incremental Learning
di: Du, Kaile, et al.
Pubblicazione: (2024)

Dynamic Prompt Adjustment for Multi-Label Class-Incremental Learning
di: Zhao, Haifeng, et al.
Pubblicazione: (2024)

Completely Weakly Supervised Class-Incremental Learning for Semantic Segmentation
di: Kim, David Minkwan, et al.
Pubblicazione: (2025)

Multimodal Parameter-Efficient Few-Shot Class Incremental Learning
di: D'Alessandro, Marco, et al.
Pubblicazione: (2023)

Versatile Incremental Learning: Towards Class and Domain-Agnostic Incremental Learning
di: Park, Min-Yeong, et al.
Pubblicazione: (2024)

EchoXFlow: A Beamspace Echocardiography Dataset for Cardiac Motion, Flow, and Function
di: Stenhede, Elias, et al.
Pubblicazione: (2026)

Future-Proofing Class-Incremental Learning
di: Jodelet, Quentin, et al.
Pubblicazione: (2024)

Federated Class-Incremental Learning with Prompting
di: Luo, Xin, et al.
Pubblicazione: (2023)

Class-Incremental Learning: A Survey
di: Zhou, Da-Wei, et al.
Pubblicazione: (2023)

Specifying What You Know or Not for Multi-Label Class-Incremental Learning
di: Zhang, Aoting, et al.
Pubblicazione: (2025)

Defying Imbalanced Forgetting in Class Incremental Learning
di: Xu, Shixiong, et al.
Pubblicazione: (2024)

Probing Image Compression For Class-Incremental Learning
di: Yang, Justin, et al.
Pubblicazione: (2024)

Dynamic Feature Learning and Matching for Class-Incremental Learning
di: Qiang, Sunyuan, et al.
Pubblicazione: (2024)

Closing the Oracle Gap: Increment Vector Transformation for Class Incremental Learning
di: Qiu, Zihuan, et al.
Pubblicazione: (2025)

Slightly Shift New Classes to Remember Old Classes for Video Class-Incremental Learning
di: Jiao, Jian, et al.
Pubblicazione: (2024)

From Isolation to Integration: Building an Adaptive Expert Forest for Pre-Trained Model-based Class-Incremental Learning
di: Liu, Ruiqi, et al.
Pubblicazione: (2026)