1 code implementation • WACV 2023 • Thomas Westfechtel, Hao-Wei Yeh, Qier Meng, Yusuke Mukuta, Tatsuya Harada
Firstly, it lets the domain classifier focus on features that are important for the classification, and, secondly, it couples the classification and adversarial branch more closely.
Ranked #8 on Domain Adaptation on Office-31
no code implementations • CVPR 2020 • Qier Meng, Satoh Shin'ichi
In this paper, we design a framework named "Attribute Driven Incremental Network" (ADINet), a new architecture that integrates class label prediction and attribute prediction into an incremental learning framework to boost the classification performance.
no code implementations • 26 Apr 2017 • Qier Meng, Takayuki Kitasaka, Masahiro Oda, Junji Ueno, Kensaku MORI
In this paper, we propose a new airway segmentation method from 3D chest CT volumes based on volume of interests (VOI) using gradient vector flow (GVF).