Medical Image Segmentation

Hongyi Wang (王洪艺)Less than 1 minute

Medical Image Segmentation & Active Learning & Domain Adaptive-Survey

A curated list of medical image segmentation for Active Learning. Keep updated.

📌 Introduction

✧ 基于主动学习的相关文献整理

➢ 论文汇总

1.综述

[1] <[TNNLS 2024][A Survey on Deep Active Learning:Recent Advances and New Frontiers]pdfopen in new window>

Dongyuan Li, Zhen Wang, Yankai Chen, Renhe Jiang, Wei** Ding, and Manabu Okumura.
本文定义了Deep Active Learning (DAL)任务，并总结了最具影响力的基线和广泛使用的数据集。从标注类型、查询策略、深度模型架构、学习范式和训练过程5个角度对DAL方法进行了系统的分类，并客观分析了它们的优缺点。全面总结了DAL在自然语言处理（NLP）、计算机视觉（CV）、数据挖掘（DM）等领域的主要应用；最后，在详细分析现有研究的基础上，讨论了面临的挑战和未来的发展方向。

2.CV

3.ADA

4.NLP

[1] <[JNLP 2024][Active Learning with Task Adaptation Pre-training for Speech Emotion Recognition]pdfopen in new window>

Dongyuan Li, Ying Zhang, Yusong Wang, Kotaro Funakoshi, and Manabu Okumura.

Reference

[1]https://github.com/Clearloveyuan/awesome-active-learning-New/tree/main

➢ 研究团队

https://github.com/openmedlab