Výsledky vyhledávání - "Švogor, Ivan"

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Profiling and Improving the PyTorch Dataloader for high-latency Storage: A Technical Report

Autor: Svogor, Ivan, Eichenberger, Christian, Spanring, Markus, Neun, Moritz, Kopp, Michael

A growing number of Machine Learning Frameworks recently made Deep Learning accessible to a wider audience of engineers, scientists, and practitioners, by allowing straightforward use of complex neural network architectures and algorithms. However, s

Externí odkaz: http://arxiv.org/abs/2211.04908

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ROS and Buzz: consensus-based behaviors for heterogeneous teams

Autor: St-Onge, David, Varadharajan, Vivek Shankar, Li, Guannan, Svogor, Ivan, Beltrame, Giovanni

This paper address the challenges encountered by developers when deploying a distributed decision-making behavior on heterogeneous robotic systems. Many applications benefit from the use of multiple robots, but their scalability and applicability are

Externí odkaz: http://arxiv.org/abs/1710.08843

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SCALL: Software Component Allocator for Heterogeneous Embedded Systems

Autor: Svogor, Ivan, Carlson, Jan

Allocation of software components on a heterogeneous computing platform involves hard decisions; handling different types of computing units with specific processing paradigms and a number of software components which require specific resources. An a

Externí odkaz: http://arxiv.org/abs/1701.00123

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An initial performance review of software components for a heterogeneous computing platform

Autor: Švogor, Ivan

The design of embedded systems is a complex activity that involves a lot of decisions. With high performance demands of present day usage scenarios and software, they often involve energy hungry state-of-the-art computing units. While focusing on pow

Externí odkaz: http://arxiv.org/abs/1701.00117

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Two factor authentication using EEG augmented passwords

Autor: Švogor, Ivan, Kišasondi, Tonimir

The current research with EEG devices in the user authentication context has some deficiencies that address expensive equipment, the requirement of laboratory conditions and applicability. In this paper we address this issue by using widely available

Externí odkaz: http://arxiv.org/abs/1612.09423

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