Zobrazeno 1 - 10
of 33
pro vyhledávání: '"Zhao, Dan"'
Autor:
Yang, Zhiwen, Chen, Haowei, Qian, Ziniu, Zhou, Yang, Zhang, Hui, Zhao, Dan, Wei, Bingzheng, Xu, Yan
Transformer-based methods have demonstrated impressive results in medical image restoration, attributed to the multi-head self-attention (MSA) mechanism in the spatial dimension. However, the majority of existing Transformers conduct attention within
Externí odkaz:
http://arxiv.org/abs/2407.09268
Autor:
Xiao, Jingyu, Xu, Zhiyao, Zou, Qingsong, Li, Qing, Zhao, Dan, Fang, Dong, Li, Ruoyu, Tang, Wenxin, Li, Kang, Zuo, Xudong, Hu, Penghui, Jiang, Yong, Weng, Zixuan, Lyv, Michael R.
Smart homes, powered by the Internet of Things, offer great convenience but also pose security concerns due to abnormal behaviors, such as improper operations of users and potential attacks from malicious attackers. Several behavior modeling methods
Externí odkaz:
http://arxiv.org/abs/2406.10928
Autor:
Yang, Zhiwen, Chen, Haowei, Qian, Ziniu, Yi, Yang, Zhang, Hui, Zhao, Dan, Wei, Bingzheng, Xu, Yan
Although single-task medical image restoration (MedIR) has witnessed remarkable success, the limited generalizability of these methods poses a substantial obstacle to wider application. In this paper, we focus on the task of all-in-one medical image
Externí odkaz:
http://arxiv.org/abs/2405.19769
Autor:
Li, Ruoyu, Li, Qing, Lin, Tao, Zou, Qingsong, Zhao, Dan, Huang, Yucheng, Tyson, Gareth, Xie, Guorui, Jiang, Yong
Device fingerprinting can be used by Internet Service Providers (ISPs) to identify vulnerable IoT devices for early prevention of threats. However, due to the wide deployment of middleboxes in ISP networks, some important data, e.g., 5-tuples and flo
Externí odkaz:
http://arxiv.org/abs/2404.12738
Anomaly-based network intrusion detection systems (A-NIDS) use unsupervised models to detect unforeseen attacks. However, existing A-NIDS solutions suffer from low throughput, lack of interpretability, and high maintenance costs. Recent in-network in
Externí odkaz:
http://arxiv.org/abs/2403.19248
In this paper, we report the performance benchmarking results of deep learning models on MLCommons' Science cloud-masking benchmark using a high-performance computing cluster at New York University (NYU): NYU Greene. MLCommons is a consortium that de
Externí odkaz:
http://arxiv.org/abs/2403.04553
Autor:
Zhao, Dan, Samsi, Siddharth, McDonald, Joseph, Li, Baolin, Bestor, David, Jones, Michael, Tiwari, Devesh, Gadepally, Vijay
As research and deployment of AI grows, the computational burden to support and sustain its progress inevitably does too. To train or fine-tune state-of-the-art models in NLP, computer vision, etc., some form of AI hardware acceleration is virtually
Externí odkaz:
http://arxiv.org/abs/2402.18593
The Higgs boson pair production at the LHC provides a probe to the Higgs boson self-coupling. The higher-order QCD corrections in this process are sizable and must be taken into account in comparison with data. Due to the small cross section, it is n
Externí odkaz:
http://arxiv.org/abs/2402.00401
Autor:
van der Poel, Constantijn, Zhao, Dan
This paper examines the use of tensor networks, which can efficiently represent high-dimensional quantum states, in language modeling. It is a distillation and continuation of the work done in (van der Poel, 2023). To do so, we will abstract the prob
Externí odkaz:
http://arxiv.org/abs/2403.12969
Multi-legged robots with six or more legs are not in common use, despite designs with superior stability, maneuverability, and a low number of actuators being available for over 20 years. This may be in part due to the difficulty in modeling multi-le
Externí odkaz:
http://arxiv.org/abs/2310.20669