1 code implementation • 4 Jan 2024 • Jing Wu, Suiyao Chen, Qi Zhao, Renat Sergazinov, Chen Li, ShengJie Liu, Chongchao Zhao, Tianpei Xie, Hanqing Guo, Cheng Ji, Daniel Cociorva, Hakan Brunzel
Self-supervised representation learning methods have achieved significant success in computer vision and natural language processing, where data samples exhibit explicit spatial or semantic dependencies.
1 code implementation • 18 Dec 2023 • Hanqing Guo, Ye Zheng, Yin Zhang, Zhi Gao, Shiyu Zhao
In this paper, we propose a global-local MAV detector that can fuse both motion and appearance features for MAV detection under challenging conditions.
no code implementations • 20 Nov 2023 • Guangjing Wang, Ce Zhou, Yuanda Wang, Bocheng Chen, Hanqing Guo, Qiben Yan
This survey offers a holistic understanding of the prevailing transferable attacks and their impacts across different domains.
no code implementations • 13 Sep 2023 • Hanqing Guo, Xun Chen, Junfeng Guo, Li Xiao, Qiben Yan
In this work, we propose a backdoor attack MASTERKEY, to compromise the SV models.
no code implementations • 13 Sep 2023 • Hanqing Guo, Guangjing Wang, Yuanda Wang, Bocheng Chen, Qiben Yan, Li Xiao
We significantly enhance the query efficiency and reduce the cost of a successful untargeted and targeted adversarial attack by 93. 1% and 65. 5% compared with the state-of-the-art black-box attacks, using merely ~300 queries (~5 minutes) and ~1, 500 queries (~25 minutes), respectively.
no code implementations • 14 Jul 2023 • Bocheng Chen, Guangjing Wang, Hanqing Guo, Yuanda Wang, Qiben Yan
The chatbot is fine-tuned with a collection of crafted conversation sequences.
no code implementations • 28 May 2022 • Hanqing Guo, Qiben Yan, Nikolay Ivanov, Ying Zhu, Li Xiao, Eric J. Hunter
Our evaluation shows that SUPERVOICE achieves 0. 58% equal error rate in the speaker verification task, it only takes 120 ms for testing an incoming utterance, outperforming all existing speaker verification systems.
no code implementations • 14 Aug 2018 • Junhong Xu, Qiwei Liu, Hanqing Guo, Aaron Kageza, Saeed AlQarni, Shaoen Wu
Deep imitation learning enables robots to learn from expert demonstrations to perform tasks such as lane following or obstacle avoidance.
no code implementations • 22 Sep 2017 • Junhong Xu, Shangyue Zhu, Hanqing Guo, Shaoen Wu
This solution includes a suboptimal sensor policy based on sensor fusion to automatically label states encountered by a robot to avoid human supervision during training.