no code implementations • 27 Feb 2023 • Mien Van, Yuzhu Sun, Stephen Mcllvanna, Minh-Nhat Nguyen, Federico Zocco, Zhijie Liu, Hsueh-Cheng Wang
This study proposes a new distributed control method based on an adaptive fuzzy control for multiple collaborative autonomous underwater vehicles (AUVs) to track a desired formation shape within a fixed time.
no code implementations • 21 Nov 2022 • Nhat Nguyen Minh, Stephen McIlvanna, Yuzhu Sun, Yan Jin, Mien Van
We formulate the control synthesis problem as an optimal control problem that enforces control barrier function (CBF) constraints to achieve obstacle avoidance.
2 code implementations • 21 Jun 2020 • Jiemin Fang, Yuzhu Sun, Qian Zhang, Kangjian Peng, Yuan Li, Wenyu Liu, Xinggang Wang
In this paper, we propose a Fast Network Adaptation (FNA++) method, which can adapt both the architecture and parameters of a seed network (e. g. an ImageNet pre-trained network) to become a network with different depths, widths, or kernel sizes via a parameter remapping technique, making it possible to use NAS for segmentation and detection tasks a lot more efficiently.
no code implementations • ICLR 2020 • Jiemin Fang, Yuzhu Sun, Kangjian Peng, Qian Zhang, Yuan Li, Wenyu Liu, Xinggang Wang
In our experiments, we conduct FNA on MobileNetV2 to obtain new networks for both segmentation and detection that clearly out-perform existing networks designed both manually and by NAS.
1 code implementation • CVPR 2020 • Jiemin Fang, Yuzhu Sun, Qian Zhang, Yuan Li, Wenyu Liu, Xinggang Wang
We revisit the search space design in most previous NAS methods and find the number and widths of blocks are set manually.
Ranked #91 on Neural Architecture Search on ImageNet