Zobrazeno 1 - 10
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pro vyhledávání: '"Run An"'
This study focuses on incremental learning for image classification, exploring how to reduce catastrophic forgetting of all learned knowledge when access to old data is restricted due to memory or privacy constraints. The challenge of incremental lea
Externí odkaz:
http://arxiv.org/abs/2411.00430
Multi-Object Tracking (MOT) aims to associate multiple objects across video frames and is a challenging vision task due to inherent complexities in the tracking environment. Most existing approaches train and track within a single domain, resulting i
Externí odkaz:
http://arxiv.org/abs/2410.23907
Autor:
Zhang, Xiao-Min, Zhao, Run-Qing, Peng, Zhi-peng, Li, Xi-Bin, Feng, Yun-Cai, Chu, Peng-Cheng, Xing, Yi-Hang
This study extended noncanonical warm inflation to the nonminimal derivative coupling scenario. The fundamental equations, including the evolution equations and the slow roll equations of this new framework, were derived. The enlarged damping term, w
Externí odkaz:
http://arxiv.org/abs/2410.16839
Autor:
Li, Boheng, Wei, Yanhao, Fu, Yankai, Wang, Zhenting, Li, Yiming, Zhang, Jie, Wang, Run, Zhang, Tianwei
Text-to-image diffusion models are pushing the boundaries of what generative AI can achieve in our lives. Beyond their ability to generate general images, new personalization techniques have been proposed to customize the pre-trained base models for
Externí odkaz:
http://arxiv.org/abs/2410.10437
Publikováno v:
J. Phys.: Condens. Matter 37, 013002 (2025)
The non-trivial magnetic and electronic phases occurring in topological magnets are often entangled, thus leading to a variety of exotic physical properties. Recently, the BaAl$_4$-type compounds have been extensively investigated to elucidate the to
Externí odkaz:
http://arxiv.org/abs/2410.10201
Remote sensing image change detection (RSCD) is crucial for monitoring dynamic surface changes, with applications ranging from environmental monitoring to disaster assessment. While traditional CNN-based methods have improved detection accuracy, they
Externí odkaz:
http://arxiv.org/abs/2410.11580
Maritime vessel maneuvers, characterized by their inherent complexity and indeterminacy, requires vessel trajectory prediction system capable of modeling the multi-modality nature of future motion states. Conventional stochastic trajectory prediction
Externí odkaz:
http://arxiv.org/abs/2410.09550
Algorithmic efficiency is essential to reducing energy use and time taken for computational problems. Optimizing efficiency is important for tasks involving multiple resources, for example in stochastic calculations where the size of the random ensem
Externí odkaz:
http://arxiv.org/abs/2410.03163
Autor:
Luo, Jing, Luo, Run, Chen, Longze, Zhu, Liang, Ao, Chang, Li, Jiaming, Chen, Yukun, Cheng, Xin, Yang, Wen, Su, Jiayuan, Li, Chengming, Yang, Min
While closed-source Large Language Models (LLMs) demonstrate strong mathematical problem-solving abilities, open-source models continue to struggle with such tasks. To bridge this gap, we propose a data augmentation approach and introduce PersonaMath
Externí odkaz:
http://arxiv.org/abs/2410.01504
A novel theoretical model for bubble dynamics is established that simultaneously accounts for the liquid compressibility, phase transition, oscillation, migration, ambient flow field, etc. The bubble dynamics equations are presented in a unified and
Externí odkaz:
http://arxiv.org/abs/2410.00335