Zobrazeno 1 - 10
of 3 007
pro vyhledávání: '"Liu, YanFang"'
Optimal mean shift vector (OMSV)-based importance sampling methods have long been prevalent in yield estimation and optimization as an industry standard. However, most OMSV-based methods are designed heuristically without a rigorous understanding of
Externí odkaz:
http://arxiv.org/abs/2407.00711
LERENet: Eliminating Intra-class Differences for Metal Surface Defect Few-shot Semantic Segmentation
Few-shot segmentation models excel in metal defect detection due to their rapid generalization ability to new classes and pixel-level segmentation, rendering them ideal for addressing data scarcity issues and achieving refined object delineation in i
Externí odkaz:
http://arxiv.org/abs/2403.11122
In the pursuit of autonomous spacecraft proximity maneuvers and docking(PMD), we introduce a novel Bayesian actor-critic reinforcement learning algorithm to learn a control policy with the stability guarantee. The PMD task is formulated as a Markov d
Externí odkaz:
http://arxiv.org/abs/2311.03680
We present a supervised learning framework of training generative models for density estimation. Generative models, including generative adversarial networks, normalizing flows, variational auto-encoders, are usually considered as unsupervised learni
Externí odkaz:
http://arxiv.org/abs/2310.14458
Code search aims to retrieve the code snippet that highly matches the given query described in natural language. Recently, many code pre-training approaches have demonstrated impressive performance on code search. However, existing code search method
Externí odkaz:
http://arxiv.org/abs/2310.06342
Being able to efficiently obtain an accurate estimate of the failure probability of SRAM components has become a central issue as model circuits shrink their scale to submicrometer with advanced technology nodes. In this work, we revisit the classic
Externí odkaz:
http://arxiv.org/abs/2307.15773
Publikováno v:
Shipin yu jixie, Vol 40, Iss 3, Pp 173-180 (2024)
Objective: Clarify the flavor characteristics of Tremella fuciformis cultivated on herbaceous substrate. Methods: In the study T. fuciformis cultivated on herbaceous substrate was used as the research object, while samples of yellow tremella and whit
Externí odkaz:
https://doaj.org/article/8e156bbfb4234f91accd68752768b1d6
We propose a deterministic-statistical method for an inverse source problem using multiple frequency limited aperture far field data. The direct sampling method is used to obtain a disc such that it contains the compact support of the source. The Dir
Externí odkaz:
http://arxiv.org/abs/2209.08222
Autor:
Chen, Liyuan, Zhang, Zhiyuan, Yu, Lei, Peng, Jiyou, Feng, Bin, Zhao, Jun, Liu, Yanfang, Xia, Fan, Zhang, Zhen, Hu, Weigang, Wang, Jiazhou
Adaptive radiation therapy (ART) could protect organs at risk (OARs) while maintain high dose coverage to targets. However, there still lack efficient online patient QA methods. We aim to develop a clinically relevant online patient quality assurance
Externí odkaz:
http://arxiv.org/abs/2206.13688
Autor:
Yu, Lei, Zhao, Jun, Xia, Fan, Zhang, Zhiyuan, Liu, Yanfang, Zhang, Wei, Zhou, Jingjie, Wang, Jiazhou, Hu, Weigang, Zhang, Zhen
The aim of this work is to describe the technical characteristics of an AI-powered radiotherapy workflow that enables full-process automation (All-in-One), evaluate its performance implemented for on-couch initial treatment of rectal cancer, and prov
Externí odkaz:
http://arxiv.org/abs/2202.12009