Zobrazeno 1 - 10
of 239
pro vyhledávání: '"Zhou, CE"'
Autor:
Zhou, Ce, Yan, Qiben, Kent, Daniel, Wang, Guangjing, Ding, Weikang, Zhang, Ziqi, Radha, Hayder
Monocular Depth Estimation (MDE) is a pivotal component of vision-based Autonomous Driving (AD) systems, enabling vehicles to estimate the depth of surrounding objects using a single camera image. This estimation guides essential driving decisions, s
Externí odkaz:
http://arxiv.org/abs/2411.00192
Autor:
Wang, Guangjing, Wang, Juexing, Zhou, Ce, Ding, Weikang, Zeng, Huacheng, Li, Tianxing, Yan, Qiben
Expression recognition holds great promise for applications such as content recommendation and mental healthcare by accurately detecting users' emotional states. Traditional methods often rely on cameras or wearable sensors, which raise privacy conce
Externí odkaz:
http://arxiv.org/abs/2410.12811
Object detection is a crucial task in autonomous driving. While existing research has proposed various attacks on object detection, such as those using adversarial patches or stickers, the exploration of projection attacks on 3D surfaces remains larg
Externí odkaz:
http://arxiv.org/abs/2409.17403
Monocular Depth Estimation (MDE) plays a crucial role in vision-based Autonomous Driving (AD) systems. It utilizes a single-camera image to determine the depth of objects, facilitating driving decisions such as braking a few meters in front of a dete
Externí odkaz:
http://arxiv.org/abs/2409.17376
Smartphones and wearable devices have been integrated into our daily lives, offering personalized services. However, many apps become overprivileged as their collected sensing data contains unnecessary sensitive information. For example, mobile sensi
Externí odkaz:
http://arxiv.org/abs/2409.03796
Autor:
Xie, Yunfei, Zhou, Ce, Gao, Lang, Wu, Juncheng, Li, Xianhang, Zhou, Hong-Yu, Liu, Sheng, Xing, Lei, Zou, James, Xie, Cihang, Zhou, Yuyin
This paper introduces MedTrinity-25M, a comprehensive, large-scale multimodal dataset for medicine, covering over 25 million images across 10 modalities, with multigranular annotations for more than 65 diseases. These enriched annotations encompass b
Externí odkaz:
http://arxiv.org/abs/2408.02900
Artificial Intelligence (AI) systems such as autonomous vehicles, facial recognition, and speech recognition systems are increasingly integrated into our daily lives. However, despite their utility, these AI systems are vulnerable to a wide range of
Externí odkaz:
http://arxiv.org/abs/2311.11796
Autor:
Zhou, Ce
A brain-computer interface (BCI) is a system that allows a person to communicate or control the surroundings without depending on the brain's normal output pathways of peripheral nerves and muscles. A lot of successful applications have arisen utiliz
Externí odkaz:
http://arxiv.org/abs/2307.08703
Autor:
Zhou, Ce, Yan, Qiben, Yu, Zhiyuan, Dixit, Eshan, Zhang, Ning, Zeng, Huacheng, Ghanhdari, Alireza Safdari
Electric Vehicle (EV) has become one of the promising solutions to the ever-evolving environmental and energy crisis. The key to the wide adoption of EVs is a pervasive charging infrastructure, composed of both private/home chargers and public/commer
Externí odkaz:
http://arxiv.org/abs/2305.08037
Autor:
Zhou, Ce, Li, Qian, Li, Chen, Yu, Jun, Liu, Yixin, Wang, Guangjing, Zhang, Kai, Ji, Cheng, Yan, Qiben, He, Lifang, Peng, Hao, Li, Jianxin, Wu, Jia, Liu, Ziwei, Xie, Pengtao, Xiong, Caiming, Pei, Jian, Yu, Philip S., Sun, Lichao
Pretrained Foundation Models (PFMs) are regarded as the foundation for various downstream tasks with different data modalities. A PFM (e.g., BERT, ChatGPT, and GPT-4) is trained on large-scale data which provides a reasonable parameter initialization
Externí odkaz:
http://arxiv.org/abs/2302.09419