Zobrazeno 1 - 10
of 231
pro vyhledávání: '"Li, Yaochen"'
Autor:
Huang, Hanshen, Qu, Tao, Cheng, Yang, Tai, Lixuan, Eckberg, Christopher, Pan, Quanjun, Alrasheed, Abdullah, Chong, Su Kong, Dai, Bingqian, Li, Yaochen, Shu, Qingyuan, Yang, Chao-Yao, Yu, Jie-Xiang, Yin, Gen, Wang, Kang L.
Antiferromagnet is a promising candidate for the next generation spintronic devices, benefiting from its ultrafast dynamics and spontaneous zero stray field. However, the understanding of their ultrafast spin behaviors is lacking due to the challenge
Externí odkaz:
http://arxiv.org/abs/2405.04686
Autor:
Tai, Lixuan, He, Haoran, Chong, Su Kong, Zhang, Huairuo, Huang, Hanshen, Qiu, Gang, Li, Yaochen, Yang, Hung-Yu, Yang, Ting-Hsun, Dong, Xiang, Ren, Yuxing, Dai, Bingqian, Qu, Tao, Shu, Qingyuan, Pan, Quanjun, Zhang, Peng, Xue, Fei, Li, Jie, Davydov, Albert V., Wang, Kang L.
Topological insulators (TI) and magnetic topological insulators (MTI) can apply highly efficient spin-orbit torque (SOT) and manipulate the magnetization with their unique topological surface states with ultra-high efficiency. Here, we demonstrate ef
Externí odkaz:
http://arxiv.org/abs/2306.05603
3D lane detection which plays a crucial role in vehicle routing, has recently been a rapidly developing topic in autonomous driving. Previous works struggle with practicality due to their complicated spatial transformations and inflexible representat
Externí odkaz:
http://arxiv.org/abs/2210.06006
Publikováno v:
Neurocomputing, Volume 467, 7 January 2022, Pages 491-503
Video object segmentation (VOS) is an essential part of autonomous vehicle navigation. The real-time speed is very important for the autonomous vehicle algorithms along with the accuracy metric. In this paper, we propose a semi-supervised real-time m
Externí odkaz:
http://arxiv.org/abs/2110.14773
Recently, Expectation-maximization (EM) algorithm has been introduced as an effective means to solve multi-view registration problem. Most of the previous methods assume that each data point is drawn from the Gaussian Mixture Model (GMM), which is di
Externí odkaz:
http://arxiv.org/abs/2012.07002
Zero-shot learning, which aims to recognize new categories that are not included in the training set, has gained popularity owing to its potential ability in the real-word applications. Zero-shot learning models rely on learning an embedding space, w
Externí odkaz:
http://arxiv.org/abs/1907.00330
Multi-view clustering is a learning paradigm based on multi-view data. Since statistic properties of different views are diverse, even incompatible, few approaches implement multi-view clustering based on the concatenated features straightforward. Ho
Externí odkaz:
http://arxiv.org/abs/1901.10657
Multi-view point cloud registration is a hot topic in the communities of multimedia technology and artificial intelligence (AI). In this paper, we propose a framework to reconstruct the 3D models by the multi-view point cloud registration algorithm w
Externí odkaz:
http://arxiv.org/abs/1811.10026
Scene model construction based on image rendering is an indispensable but challenging technique in computer vision and intelligent transportation systems. In this paper, we propose a framework for constructing 3D corridor-based road scene models. Thi
Externí odkaz:
http://arxiv.org/abs/1811.09790
Aggregating deep convolutional features into a global image vector has attracted sustained attention in image retrieval. In this paper, we propose an efficient unsupervised aggregation method that uses an adaptive Gaussian filter and an elementvalue
Externí odkaz:
http://arxiv.org/abs/1803.07360