The success of deep learning methods in medical image segmentation tasks usually requires a large amount of labeled data. However, obtaining reliable annotations is expensive and time-consuming. Semi-supervised learning has attracted much attention in medical image segmentation by taking the advantage of...
We motivate the problem setting and our regularized dual-task learning approach by industrial use cases, e.g. gas or wind turbine modeling for optimization and monitoring. Then, we formalize the problem and describe our regularization term by which the learning objective of the Factored Tensor ...
The success of deep learning methods in medical image segmentation tasks usually requires a large amount of labeled data. However, obtaining reliable annotations is expensive and time-consuming. Semi-supervised learning has attracted much attention in me
the reliance on anomaly detection to preempt equipment malfunctions faces the challenge of sudden anomaly discernment. To address this challenge, this paper proposes a dual-task learning approach
Simultaneous Partial Discharge Diagnosis and Localization in Gas-Insulated Switchgear via a Dual-Task Learning Network doi:10.1109/TPWRD.2023.3312704Partial dischargediagnosis and localizationdual-task networkmultigate mixture-of-expertsgas-insulated switchgearDiagnosis and location of partial discharge (PD) are...
Dual-task learning with tailored loss functions improves the learning capability of the proposed model. Abstract Background and Objective Multi-class cancer classification has been extensively studied in digital and computational pathology due to its importance in clinical decision-making. Numerous computatio...
近日,顶级国际会议 NeurIPS 的 The Machine Learning for Combinatorial Optimization(以下简称:ML4CO) 组合优化比赛结果揭幕,来自旷视研究院的代表队荣获 Dual Task 赛道冠军。 ML4CO 全称基于机器学习的组合优化,本次比赛由加拿大蒙特利尔理工大学和蒙特利尔大学机器学习研究所 (Mila) 主办。Mila是全球领先的深度学习研究...
1. 双任务 在一项双任务(dual-task)研究中,Baddeley 以国际象棋大师和新手为两组被试, 让他们完成回忆棋子位置和下象棋的任务, … www.docin.com|基于10个网页 2. 双重任务 对这一问题的研究大多是采用双重任务(dual-task)的方法,将保持直立姿势的稳定作为实验主任务,与姿势控制无直接关联的认知 … ...
In this paper, we introduce the interactive learning network (DTIL-Net) for automated grading of DR and DME. DTIL-Net aims to explore and exploit the potential correlation between DR and DME. It consists of two main components: the attention module (AM) and the dual branch exchange module...
Traditional methods in this domain are based on template algorithms; others are based on cascaded regression, while the methods based on deep learning are nowadays almost the recent trends. According to this categorization, we succinctly review in this section some of the recent advanced studies. ...