no code implementations • 26 Jan 2024 • Zhenliang Zhang, Zeyu Zhang, Ziyuan Jiao, Yao Su, Hangxin Liu, Wei Wang, Song-Chun Zhu
Artificial intelligence (AI) has revolutionized human cognitive abilities and facilitated the development of new AI entities capable of interacting with humans in both physical and virtual environments.
no code implementations • 4 Nov 2023 • Hang Yin, Yao Su, Xinyue Liu, Thomas Hartvigsen, Yanhua Li, Xiangnan Kong
We refer to such brain networks as multi-state, and this mixture can help us understand human behavior.
no code implementations • 5 Oct 2023 • Yilue Qian, Peiyu Yu, Ying Nian Wu, Yao Su, Wei Wang, Lifeng Fan
In this paper, we propose an interpretable and generalizable visual planning framework consisting of i) a novel Substitution-based Concept Learner (SCL) that abstracts visual inputs into disentangled concept representations, ii) symbol abstraction and reasoning that performs task planning via the self-learned symbols, and iii) a Visual Causal Transition model (ViCT) that grounds visual causal transitions to semantically similar real-world actions.
1 code implementation • 27 Jul 2023 • Yao Su, Zhentian Qian, Lei Ma, Lifang He, Xiangnan Kong
Brain extraction, registration and segmentation are indispensable preprocessing steps in neuroimaging studies.
1 code implementation • 6 Dec 2022 • Yao Su, Zhentian Qian, Lifang He, Xiangnan Kong
Our code and data can be found at https://github. com/ERNetERNet/ERNet
1 code implementation • 6 Dec 2022 • Yao Su, Xin Dai, Lifang He, Xiangnan Kong
Recent research on deformable image registration is mainly focused on improving the registration accuracy using multi-stage alignment methods, where the source image is repeatedly deformed in stages by a same neural network until it is well-aligned with the target image.