Zobrazeno 1 - 10
of 63
pro vyhledávání: '"Lau, Chun Pong"'
Neural networks have achieved remarkable performance across a wide range of tasks, yet they remain susceptible to adversarial perturbations, which pose significant risks in safety-critical applications. With the rise of multimodality, diffusion model
Externí odkaz:
http://arxiv.org/abs/2410.14089
Neural networks, despite their remarkable performance in widespread applications, including image classification, are also known to be vulnerable to subtle adversarial noise. Although some diffusion-based purification methods have been proposed, for
Externí odkaz:
http://arxiv.org/abs/2408.17064
Autor:
Lau, Chun Pong
In dynamic discrete choice models, some parameters, such as the discount factor, are being fixed instead of being estimated. This paper proposes two sensitivity analysis procedures for dynamic discrete choice models with respect to the fixed paramete
Externí odkaz:
http://arxiv.org/abs/2408.16330
Autor:
Guo, Zhongliang, Fang, Lei, Lin, Jingyu, Qian, Yifei, Zhao, Shuai, Wang, Zeyu, Dong, Junhao, Chen, Cunjian, Arandjelović, Ognjen, Lau, Chun Pong
Recent advancements in generative AI, particularly Latent Diffusion Models (LDMs), have revolutionized image synthesis and manipulation. However, these generative techniques raises concerns about data misappropriation and intellectual property infrin
Externí odkaz:
http://arxiv.org/abs/2408.10901
6G networks are envisioned to deliver a large diversity of applications and meet stringent quality of service (QoS) requirements. Hence, integrated terrestrial and non-terrestrial networks (TN-NTNs) are anticipated to be key enabling technologies. Ho
Externí odkaz:
http://arxiv.org/abs/2312.01895
In this paper, we address the challenging task of whole-body biometric detection, recognition, and identification at distances of up to 500m and large pitch angles of up to 50 degree. We propose an end-to-end system evaluated on diverse datasets, inc
Externí odkaz:
http://arxiv.org/abs/2311.05725
Autor:
Lau, Chun Pong
The flexibility of future mobile networks exploiting modern technologies such as cloud-optimized radio access and software-defined networks opens a gateway to deploying dynamic strategies for live and on-demand content delivery. Traditional live broa
Externí odkaz:
http://hdl.handle.net/10754/628039
Gait recognition holds the promise of robustly identifying subjects based on walking patterns instead of appearance information. While previous approaches have performed well for curated indoor data, they tend to underperform in unconstrained situati
Externí odkaz:
http://arxiv.org/abs/2307.14578
The increasingly pervasive facial recognition (FR) systems raise serious concerns about personal privacy, especially for billions of users who have publicly shared their photos on social media. Several attempts have been made to protect individuals f
Externí odkaz:
http://arxiv.org/abs/2305.13625
The increasingly pervasive facial recognition (FR) systems raise serious concerns about personal privacy, especially for billions of users who have publicly shared their photos on social media. Several attempts have been made to protect individuals f
Externí odkaz:
http://arxiv.org/abs/2305.13548