Zobrazeno 1 - 10
of 4 770
pro vyhledávání: '"Wang, XinXin"'
Autor:
Li, Qiao, Wu, Cong, Chen, Jing, Zhang, Zijun, He, Kun, Du, Ruiying, Wang, Xinxin, Zhao, Qingchuang, Liu, Yang
Deep neural networks (DNNs) are increasingly used in critical applications such as identity authentication and autonomous driving, where robustness against adversarial attacks is crucial. These attacks can exploit minor perturbations to cause signifi
Externí odkaz:
http://arxiv.org/abs/2408.10647
Recent studies emphasize the crucial role of data augmentation in enhancing the performance of object detection models. However,existing methodologies often struggle to effectively harmonize dataset diversity with semantic coordination.To bridge this
Externí odkaz:
http://arxiv.org/abs/2408.02891
Autor:
Feng, Zihao, Jiang, Yuanyuan, Zhang, Liyang, Liu, Zhigang, Wang, Kai, Wang, Xinxin, Zou, Xiaobing, Luo, Haiyun, Fu, Yangyang
Publikováno v:
Appl. Phys. Lett. 125, 134101 (2024)
Direct current (DC) gas insulated transmission lines (GILs) have been widely used in power transmission, but might be threatened by partial discharge due to the presence of floating impurities (e.g., dust and metal particles) inside the sealed chambe
Externí odkaz:
http://arxiv.org/abs/2406.18358
Autor:
Fendor, Zuzanna, van der Velden, Bas H. M., Wang, Xinxin, Carnoli, Andrea Jr., Mutlu, Osman, Hürriyetoğlu, Ali
Research in the food domain is at times limited due to data sharing obstacles, such as data ownership, privacy requirements, and regulations. While important, these obstacles can restrict data-driven methods such as machine learning. Federated learni
Externí odkaz:
http://arxiv.org/abs/2406.06202
Autor:
Wang, Xinxin, Yu, Ye-Zhao
Fast radio bursts are a class of transient radio sources that are thought to originate from extragalactic sources since their dispersion measure greatly exceeds the highest dispersion measure that the Milky Way interstellar medium can provide. Host G
Externí odkaz:
http://arxiv.org/abs/2309.07751
In the context of reducing carbon emissions in the automotive supply chain, collaboration between vehicle manufacturers and retailers has proven to be an effective measure for enhancing carbon emission reduction within the enterprise. This study aims
Externí odkaz:
http://arxiv.org/abs/2306.07211
Autor:
Wu, Yuting, Wang, Qiwen, Wang, Ziyu, Wang, Xinxin, Ayyagari, Buvna, Krishnan, Siddarth, Chudzik, Michael, Lu, Wei D.
Publikováno v:
Adv. Mater.35 (2023) 2305465
The need for deep neural network (DNN) models with higher performance and better functionality leads to the proliferation of very large models. Model training, however, requires intensive computation time and energy. Memristor-based compute-in-memory
Externí odkaz:
http://arxiv.org/abs/2305.14547
Autor:
Wang, Ziyu, Wu, Yuting, Park, Yongmo, Yoo, Sangmin, Wang, Xinxin, Eshraghian, Jason K., Lu, Wei D.
Analog compute-in-memory (CIM) systems are promising for deep neural network (DNN) inference acceleration due to their energy efficiency and high throughput. However, as the use of DNNs expands, protecting user input privacy has become increasingly i
Externí odkaz:
http://arxiv.org/abs/2304.11056
Event-based cameras are inspired by the sparse and asynchronous spike representation of the biological visual system. However, processing the event data requires either using expensive feature descriptors to transform spikes into frames, or using spi
Externí odkaz:
http://arxiv.org/abs/2303.10770
Same-style products retrieval plays an important role in e-commerce platforms, aiming to identify the same products which may have different text descriptions or images. It can be used for similar products retrieval from different suppliers or duplic
Externí odkaz:
http://arxiv.org/abs/2302.05093