4 citations · 6 across the 6 of their papers we have counts for
9 papers
Understanding Knowledge Transferability for Transfer Learning: A Survey
Haohua Wang, Jingge Wang, Zijie Zhao +9
Transfer learning has become an essential paradigm in artificial intelligence, enabling the transfer of knowledge from a source task to improve performance on a target task. This a…
TMT: Cross-domain Semantic Segmentation with Region-adaptive Transferability Estimation
Enming Zhang, Zhengyu Li, Yanru Wu +5
Recent advances in Vision Transformers (ViTs) have significantly advanced semantic segmentation performance. However, their adaptation to new target domains remains challenged by d…
Transfer Risk Map: Mitigating Pixel-level Negative Transfer in Medical Segmentation
Shutong Duan, Jingyun Yang, Yang Tan +3
How to mitigate negative transfer in transfer learning is a long-standing and challenging issue, especially in the application of medical image segmentation. Existing methods for r…
Exploiting Task Relationships in Continual Learning via Transferability-Aware Task Embeddings
Yanru Wu, Jianning Wang, Xiangyu Chen +4
Continual learning (CL) has been a critical topic in contemporary deep neural network applications, where higher levels of both forward and backward transfer are desirable for an e…
Finding the Most Transferable Tasks for Brain Image Segmentation
Yicong Li, Yang Tan, Jingyun Yang +2
Although many studies have successfully applied transfer learning to medical image segmentation, very few of them have investigated the selection strategy when multiple source task…
Transferability-Guided Cross-Domain Cross-Task Transfer Learning
Yang Tan, Enming Zhang, Yang Li +2
We propose two novel transferability metrics F-OTCE (Fast Optimal Transport based Conditional Entropy) and JC-OTCE (Joint Correspondence OTCE) to evaluate how much the source model…
Transferability Estimation for Semantic Segmentation Task
Yang Tan, Yang Li, Shao-Lun Huang
Transferability estimation is a fundamental problem in transfer learning to predict how good the performance is when transferring a source model (or source task) to a target task.…
Practical Transferability Estimation for Image Classification Tasks
Yang Tan, Yang Li, Shao-Lun Huang
Transferability estimation is an essential problem in transfer learning to predict how good the performance is when transferring a source model (or source task) to a target task. R…
OTCE: A Transferability Metric for Cross-Domain Cross-Task Representations
Yang Tan, Yang Li, Shao-Lun Huang
Transfer learning across heterogeneous data distributions (a.k.a. domains) and distinct tasks is a more general and challenging problem than conventional transfer learning, where e…