Výsledky vyhledávání - "Siebert, Jan"

Elektronická kniha

Effizienzoptimierung mobilhydraulischer Load-Sensing-Systeme durch Reduzierung systembedingter Druckverluste am Beispiel eines Hydraulikbaggers

Autor: Siebert, Jan

In this thesis, a hydraulic circuit will be developed, which can reduce the partial load losses of hydraulic-mechanic load-sensing systems (LS). As reference application, the LS system of an hydraulic excavator will be used. The efficiency improvemen

Externí odkaz: https://library.oapen.org/handle/20.500.12657/93283

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Conference

Reduction of System Inherent Pressure Losses at Pressure Compensators of Hydraulic Load Sensing Systems

Autor: Siebert, Jan, Geimer, Marcus

Publikováno v: 10th International Fluid Power Conference (10. IFK) March 8-10, 2016. 1:253-266

In spite of their high technical maturity, load sensing systems (LS) have system-inherent energy losses that are largely due to the operation of parallel actuators with different loads at the same pressure level. Hereby, the pressure compensators of

Externí odkaz: https://tud.qucosa.de/id/qucosa%3A28268
https://tud.qucosa.de/api/qucosa%3A28268/attachment/ATT-0/

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Kniha

Ratingagenturen auf den internationalen Finanzmärkten : ihre rolle in der finanz- und eurokrise / Jan Siebert. [elektronicky zdroj]

Autor: Siebert, Jan, author

Externí odkaz: Kolekce e-knih KNAV

Kniha

Konzernrechnungslegung [elektronicky zdroj] : die Regelung nach HGB und IFRS / Jan Siebert.

Autor: Siebert, Jan

Externí odkaz: Kolekce e-knih KNAV

Report

Fully Convolutional Networks for Automatically Generating Image Masks to Train Mask R-CNN

Autor: Wu, Hao, Siebert, Jan Paul, Xu, Xiangrong

This paper proposes a novel automatically generating image masks method for the state-of-the-art Mask R-CNN deep learning method. The Mask R-CNN method achieves the best results in object detection until now, however, it is very time-consuming and la

Externí odkaz: http://arxiv.org/abs/2003.01383

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Akademický článek

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Report

Efficient Egocentric Visual Perception Combining Eye-tracking, a Software Retina and Deep Learning

Autor: Hristozova, Nina, Ozimek, Piotr, Siebert, Jan Paul

We present ongoing work to harness biological approaches to achieving highly efficient egocentric perception by combining the space-variant imaging architecture of the mammalian retina with Deep Learning methods. By pre-processing images collected by

Externí odkaz: http://arxiv.org/abs/1809.01633

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