no code implementations • 15 Feb 2024 • Zhizhang Yuan, Daoze Zhang, Junru Chen, Gefei Gu, Yang Yang
Foundational models benefit from pre-training on large amounts of unlabeled data and enable strong performance in a wide variety of applications with a small amount of labeled data.
no code implementations • 1 Feb 2024 • Fanzhe Fu, Junru Chen, Jing Zhang, Carl Yang, Lvbin Ma, Yang Yang
Time-series data presents limitations stemming from data quality issues, bias and vulnerabilities, and generalization problem.
no code implementations • 15 Jun 2023 • Donghong Cai, Junru Chen, Yang Yang, Teng Liu, Yafeng Li
Intuitively, brain signals, generated by the firing of neurons, are transmitted among different connecting structures in human brain.
no code implementations • 15 Jun 2023 • Junru Chen, Yang Yang, Tao Yu, Yingying Fan, Xiaolong Mo, Carl Yang
Therefore, we propose the first data-driven study to detect epileptic waves in a real-world SEEG dataset.
1 code implementation • 12 Sep 2022 • Haobo Chen, Chuyang Zhao, Kai Tu, Junru Chen, Yadong Li, Boxun Li
In this paper, we first verify through an experiment that style factors are a vital part of domain bias.
Domain Generalization Generalizable Person Re-identification +1
1 code implementation • 22 Jun 2022 • Chuyang Zhao, Haobo Chen, Wenyuan Zhang, Junru Chen, Sipeng Zhang, Yadong Li, Boxun Li
Natural language (NL) based vehicle retrieval aims to search specific vehicle given text description.
no code implementations • 30 Apr 2021 • Junru Chen, Shiqing Geng, Yongluan Yan, Danyang Huang, Hao liu, Yadong Li
Vehicle Re-identification aims to identify a specific vehicle across time and camera view.
no code implementations • 4 Dec 2020 • Jiarong Xu, Yang Yang, Junru Chen, Chunping Wang, Xin Jiang, Jiangang Lu, Yizhou Sun
Additionally, we explore a provable connection between the robustness of the unsupervised graph encoder and that of models on downstream tasks.
no code implementations • 13 May 2020 • Chaoran Zhuge, Yujie Peng, Yadong Li, Jiangbo Ai, Junru Chen
Vehicle re-identification is one of the core technologies of intelligent transportation systems and smart cities, but large intra-class diversity and inter-class similarity poses great challenges for existing method.