no code implementations • 30 Jan 2023 • Zhize Wu, Changjiang Du, Le Zou, Ming Tan, Tong Xu, Fan Cheng, Fudong Nian, Thomas Weise
This so-called domain shift leads to a significant performance drop in image classification.
no code implementations • 12 Feb 2022 • Zhize Wu, XiaoFeng Wang, Tong Xu, Xuebin Yang, Le Zou, Lixiang Xu, Thomas Weise
We embed a domain classification network in the region proposal network~(RPN) using adversarial learning.
no code implementations • 1 Dec 2021 • Thomas Weise, Zhize Wu, Xinlu Li, Yan Chen, Jörg Lässig
A fitness assignment process transforms the features (such as the objective value) of a candidate solution to a scalar fitness, which then is the basis for selection.
no code implementations • 7 Jul 2020 • Thomas Bartz-Beielstein, Carola Doerr, Daan van den Berg, Jakob Bossek, Sowmya Chandrasekaran, Tome Eftimov, Andreas Fischbach, Pascal Kerschke, William La Cava, Manuel Lopez-Ibanez, Katherine M. Malan, Jason H. Moore, Boris Naujoks, Patryk Orzechowski, Vanessa Volz, Markus Wagner, Thomas Weise
This survey compiles ideas and recommendations from more than a dozen researchers with different backgrounds and from different institutes around the world.
no code implementations • 12 Mar 2020 • Zhize Wu, Thomas Weise, Le Zou, Fei Sun, Ming Tan
Differing from the previous studies, we propose a new method called Denoising Autoencoder with Temporal and Categorical Constraints (DAE_CTC)} to study the skeletal representation in a view of skeleton reconstruction.
no code implementations • 6 Jan 2020 • Thomas Weise, Zhize Wu, Xinlu Li, Yan Chen
Since Jump and Trap are bijective transformations of OneMax, it behaves identical on all three.
no code implementations • 23 Jun 2018 • Thomas Weise, Zijun Wu, Markus Wagner
We propose using more advanced methods to discriminate between "good" and "bad" sample runs, with the goal of increasing the correlation of the chosen run with the a-posteriori best one.