no code implementations • 2 Apr 2019 • Lvchen Cao, Huiqi Li, Yanjun Zhang, Liang Xu, Li Zhang
In this paper, a feature extraction-based method for grading cataract severity using retinal images is proposed.
no code implementations • 2 Dec 2020 • Yiming Gan, Yu Bo, Boyuan Tian, Leimeng Xu, Wei Hu, Shaoshan Liu, Qiang Liu, Yanjun Zhang, Jie Tang, Yuhao Zhu
We develop and commercialize autonomous machines, such as logistic robots and self-driving cars, around the globe.
Self-Driving Cars Hardware Architecture
no code implementations • 1 Apr 2021 • Zishen Wan, Yuyang Zhang, Arijit Raychowdhury, Bo Yu, Yanjun Zhang, Shaoshan Liu
In our past few years' of commercial deployment experiences, we identify localization as a critical task in autonomous machine applications, and a great acceleration target.
no code implementations • 11 Apr 2021 • Tian Gao, Zishen Wan, Yuyang Zhang, Bo Yu, Yanjun Zhang, Shaoshan Liu, Arijit Raychowdhury
Stereo matching is a critical task for robot navigation and autonomous vehicles, providing the depth estimation of surroundings.
no code implementations • 27 Apr 2021 • Yanjun Zhang, Guangdong Bai, Xue Li, Surya Nepal, Ryan K L Ko
We prove that less information is exposed in CGD compared to that of traditional FL.
1 code implementation • 18 Apr 2023 • Xiaomei Zhang, Zhaoxi Zhang, Qi Zhong, Xufei Zheng, Yanjun Zhang, Shengshan Hu, Leo Yu Zhang
To explore how to use the masked language model in adversarial detection, we propose a novel textual adversarial example detection method, namely Masked Language Model-based Detection (MLMD), which can produce clearly distinguishable signals between normal examples and adversarial examples by exploring the changes in manifolds induced by the masked language model.
no code implementations • 14 Sep 2023 • Jiaheng Wei, Yanjun Zhang, Leo Yu Zhang, Chao Chen, Shirui Pan, Kok-Leong Ong, Jun Zhang, Yang Xiang
For the first time, we show the feasibility of a client-side adversary with limited knowledge being able to recover the training samples from the aggregated global model.
no code implementations • 13 Nov 2023 • Zirui Gong, Liyue Shen, Yanjun Zhang, Leo Yu Zhang, Jingwei Wang, Guangdong Bai, Yong Xiang
By equipping AGRAMPLIFIER with the existing Byzantine-robust mechanisms, we successfully enhance the model's robustness, maintaining its fidelity and improving overall efficiency.
no code implementations • 17 Apr 2024 • Hangtao Zhang, Shengshan Hu, Yichen Wang, Leo Yu Zhang, Ziqi Zhou, Xianlong Wang, Yanjun Zhang, Chao Chen
This paper is dedicated to bridging this gap by introducing Detector Collapse} (DC), a brand-new backdoor attack paradigm tailored for object detection.