Zobrazeno 1 - 3
of 3
pro vyhledávání: '"Qutub, Syed Sha"'
Autor:
Qutub, Syed Sha, Kose, Neslihan, Rosales, Rafael, Paulitsch, Michael, Hagn, Korbinian, Geissler, Florian, Peng, Yang, Hinz, Gereon, Knoll, Alois
This paper introduces the Budding Ensemble Architecture (BEA), a novel reduced ensemble architecture for anchor-based object detection models. Object detection models are crucial in vision-based tasks, particularly in autonomous systems. They should
Externí odkaz:
http://arxiv.org/abs/2309.08036
Publikováno v:
Deep Neural Networks and Data for Automated Driving ISBN: 9783031012327
This chapter introduces a novel data synthesis framework for validation of perception functions based on machine learning to ensure the safety and functionality of these systems, specifically in the context of automated driving. The main contribution
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::04cf02ad7e85d11fd1160170f9006e9b
https://doi.org/10.1007/978-3-031-01233-4_13
https://doi.org/10.1007/978-3-031-01233-4_13
Publikováno v:
CSCS
This contribution discusses the use of variational data synthesis as a tool to analyze and understand limitations of performance of DNNs (deep neural networks) in perception tasks. To date, no universally accepted methodologies for validating ML (Mac
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5675cfe743c6db985492a52c90815b6f
https://doi.org/10.1145/3385958.3430479
https://doi.org/10.1145/3385958.3430479
