Zobrazeno 1 - 10
of 941 394
pro vyhledávání: '"input data"'
We study how the choice of input data affects simulations of positive streamers in humid air, focusing on H2O cross sections, photoionization models, and chemistry sets. Simulations are performed in air with a mole fraction of 0%, 3% or 10% H2O using
Externí odkaz:
http://arxiv.org/abs/2412.03861
Autor:
Rezaei, Ehsan Eyshi1 (AUTHOR) EhsanEyshi.Rezaei@zalf.de, Faye, Babacar1,2 (AUTHOR), Ewert, Frank1,3 (AUTHOR), Asseng, Senthold4 (AUTHOR), Martre, Pierre5 (AUTHOR), Webber, Heidi1,6 (AUTHOR)
Publikováno v:
Scientific Reports. 10/5/2024, Vol. 14 Issue 1, p1-11. 11p.
Autor:
Ramesh, Rahul, Bisulco, Anthony, DiTullio, Ronald W., Wei, Linran, Balasubramanian, Vijay, Daniilidis, Kostas, Chaudhari, Pratik
We show that many perception tasks, from visual recognition, semantic segmentation, optical flow, depth estimation to vocalization discrimination, are highly redundant functions of their input data. Images or spectrograms, projected into different su
Externí odkaz:
http://arxiv.org/abs/2407.13841
Modelling uncertainty in Machine Learning models is essential for achieving safe and reliable predictions. Most research on uncertainty focuses on output uncertainty (predictions), but minimal attention is paid to uncertainty at inputs. We propose a
Externí odkaz:
http://arxiv.org/abs/2406.18787
Autor:
Wang, Chengguan1 (AUTHOR) wangchengguan@szpu.edu.cn, Wang, Guangping2 (AUTHOR) wanggp005@avic.com, Wang, Tao3 (AUTHOR) charlietree@szpu.edu.cn, Xiong, Xiyao2 (AUTHOR) xiongxy003@avic.com, Ouyang, Zhongchuan2 (AUTHOR) ouyzc@avic.com, Gong, Tao1,3 (AUTHOR) charlietree@szpu.edu.cn
Publikováno v:
Sensors (14248220). Aug2024, Vol. 24 Issue 16, p5300. 33p.
Akademický článek
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The input data pipeline is an essential component of each machine learning (ML) training job. It is responsible for reading massive amounts of training data, processing batches of samples using complex transformations, and loading them onto training
Externí odkaz:
http://arxiv.org/abs/2401.08895
Akademický článek
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Publikováno v:
Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries. BrainLes 2015
In machine learning larger databases are usually associated with higher classification accuracy due to better generalization. This generalization may lead to non-optimal classifiers in some medical applications with highly variable expressions of pat
Externí odkaz:
http://arxiv.org/abs/2403.07428