Zobrazeno 1 - 10
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pro vyhledávání: '"Shekar, Arvind Kumar"'
Unsupervised semantic segmentation requires assigning a label to every pixel without any human annotations. Despite recent advances in self-supervised representation learning for individual images, unsupervised semantic segmentation with pixel-level
Externí odkaz:
http://arxiv.org/abs/2203.13868
Publikováno v:
2021 20th IEEE International Conference on Machine Learning and Applications (ICMLA)
The advent of Convolutional Neural Networks (CNNs) has led to their application in several domains. One noteworthy application is the perception system for autonomous driving that relies on the predictions from CNNs. Practitioners evaluate the genera
Externí odkaz:
http://arxiv.org/abs/2201.00531
Autor:
Gou, Liang, Zou, Lincan, Li, Nanxiang, Hofmann, Michael, Shekar, Arvind Kumar, Wendt, Axel, Ren, Liu
Traffic light detection is crucial for environment perception and decision-making in autonomous driving. State-of-the-art detectors are built upon deep Convolutional Neural Networks (CNNs) and have exhibited promising performance. However, one loomin
Externí odkaz:
http://arxiv.org/abs/2009.12975
Predicting the health of components in complex dynamic systems such as an automobile poses numerous challenges. The primary aim of such predictive systems is to use the high-dimensional data acquired from different sensors and predict the state-of-he
Externí odkaz:
http://arxiv.org/abs/1804.05544
Autor:
Shekar, Arvind Kumar1 (AUTHOR) arvindkumar.shekar@de.bosch.com, Gou, Liang2 (AUTHOR), Ren, Liu2 (AUTHOR), Wendt, Axel1 (AUTHOR)
Publikováno v:
International Journal of Computer Vision. Apr2021, Vol. 129 Issue 4, p1185-1201. 17p.
Akademický článek
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Publikováno v:
IEEE Transactions on Visualization and Computer Graphics; January 2023, Vol. 29 Issue: 1 p74-83, 10p
Akademický článek
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Autor:
Rebelo de Sá, Claudio, Shekar, Arvind Kumar, Ferreira, Hugo, Soares, Carlos, Quintián, Héctor, Sáez Muñoz, José António, Corchado, Emilio, Martínez Álvarez, Francisco, Troncoso Lora, Alicia
Publikováno v:
Advances in Intelligent Systems and Computing ISBN: 9783030200541
SOCO
14th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2019), 142-153
STARTPAGE=142;ENDPAGE=153;TITLE=14th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2019)
SOCO
14th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2019), 142-153
STARTPAGE=142;ENDPAGE=153;TITLE=14th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2019)
Sensors are susceptible to failure when exposed to extreme conditions over long periods of time. Besides they can be affected by noise or electrical interference. Models (Machine Learning or others) obtained from these faulty and noisy sensors may be
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a7530df0e447448e5a17e6ed88a536a2
https://doi.org/10.1007/978-3-030-20055-8_14
https://doi.org/10.1007/978-3-030-20055-8_14