Zobrazeno 1 - 10
of 1 828
pro vyhledávání: '"Zhang, Zilong"'
Vision-based industrial inspection (VII) aims to locate defects quickly and accurately. Supervised learning under a close-set setting and industrial anomaly detection, as two common paradigms in VII, face different problems in practical applications.
Externí odkaz:
http://arxiv.org/abs/2407.21351
Learning a universal manipulation policy encompassing doors with diverse categories, geometries and mechanisms, is crucial for future embodied agents to effectively work in complex and broad real-world scenarios. Due to the limited datasets and unrea
Externí odkaz:
http://arxiv.org/abs/2403.02604
Electromagnetic radiation at higher harmonics of the plasma frequency ($\omega \sim n\omega_{pe}, n > 2$) has been occasionally observed in type II and type III solar radio bursts, yet the underlying mechanism remains undetermined. Here we present tw
Externí odkaz:
http://arxiv.org/abs/2312.13617
One-class classification (OCC), i.e., identifying whether an example belongs to the same distribution as the training data, is essential for deploying machine learning models in the real world. Adapting the pre-trained features on the target dataset
Externí odkaz:
http://arxiv.org/abs/2309.01483
Autor:
Kan, Xuan, Li, Zimu, Cui, Hejie, Yu, Yue, Xu, Ran, Yu, Shaojun, Zhang, Zilong, Guo, Ying, Yang, Carl
Biological networks are commonly used in biomedical and healthcare domains to effectively model the structure of complex biological systems with interactions linking biological entities. However, due to their characteristics of high dimensionality an
Externí odkaz:
http://arxiv.org/abs/2306.02532
Industrial anomaly detection (IAD) is crucial for automating industrial quality inspection. The diversity of the datasets is the foundation for developing comprehensive IAD algorithms. Existing IAD datasets focus on the diversity of data categories,
Externí odkaz:
http://arxiv.org/abs/2304.02216
Publikováno v:
Journal of Financial & Quantitative Analysis; Aug2024, Vol. 59 Issue 5, p2099-2132, 34p
According to the standard scenario of plasma emission, escaping radiations are generated by the nonlinear development of the kinetic bump-on-tail instability driven by a single beam of energetic electrons interacting with plasmas. Here we conduct ful
Externí odkaz:
http://arxiv.org/abs/2210.16503
Human brains are commonly modeled as networks of Regions of Interest (ROIs) and their connections for the understanding of brain functions and mental disorders. Recently, Transformer-based models have been studied over different types of data, includ
Externí odkaz:
http://arxiv.org/abs/2210.06681
The standard theory of plasma emission is based on kinetic couplings between a single beam of energetic electrons and unmagnetized thermal plasmas, involving multi-step nonlinear wave-particle and wave-wave interactions. The theory has not yet been c
Externí odkaz:
http://arxiv.org/abs/2209.11707