Zobrazeno 1 - 10
of 14
pro vyhledávání: '"Payman Goodarzi"'
Autor:
Yannick Robin, Johannes Amann, Payman Goodarzi, Tizian Schneider, Andreas Schütze, Christian Bur
Publikováno v:
Atmosphere, Vol 13, Iss 10, p 1614 (2022)
In this study, methods from the field of deep learning are used to calibrate a metal oxide semiconductor (MOS) gas sensor in a complex environment in order to be able to predict a specific gas concentration. Specifically, we want to tackle the proble
Externí odkaz:
https://doaj.org/article/80f26bd7669e458489537d597f875fd6
Autor:
Christopher Schnur, Payman Goodarzi, Yevgeniya Lugovtsova, Jannis Bulling, Jens Prager, Kilian Tschöke, Jochen Moll, Andreas Schütze, Tizian Schneider
Publikováno v:
Sensors, Vol 22, Iss 1, p 406 (2022)
Data-driven analysis for damage assessment has a large potential in structural health monitoring (SHM) systems, where sensors are permanently attached to the structure, enabling continuous and frequent measurements. In this contribution, we propose a
Externí odkaz:
https://doaj.org/article/5996091073a8414a904a7f4154388676
Autor:
Yannick Robin, Johannes Amann, Tobias Baur, Payman Goodarzi, Caroline Schultealbert, Tizian Schneider, Andreas Schütze
Publikováno v:
Atmosphere, Vol 12, Iss 11, p 1487 (2021)
With air quality being one target in the sustainable development goals set by the United Nations, accurate monitoring also of indoor air quality is more important than ever. Chemiresistive gas sensors are an inexpensive and promising solution for the
Externí odkaz:
https://doaj.org/article/32de8cf28a6340d7a1a1ee0c236072a7
Publikováno v:
Applied Sciences, Vol 11, Iss 5, p 2199 (2021)
Trust in artificial intelligence (AI) predictions is a crucial point for a widespread acceptance of new technologies, especially in sensitive areas like autonomous driving. The need for tools explaining AI for deep learning of images is thus eminent.
Externí odkaz:
https://doaj.org/article/a15331689eac47c084ba2f24941e10d0
Publikováno v:
tm - Technisches Messen. 89:224-239
Nowadays machine learning methods and data-driven models have been used widely in different fields including computer vision, biomedicine, and condition monitoring. However, these models show performance degradation when meeting real-life situations.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cd9da6486dafe4cf3b976e48c31095f6
https://doi.org/10.1515/teme-2021-0129
https://doi.org/10.1515/teme-2021-0129
Autor:
Andreas Schütze, Payman Goodarzi, Yannick Robin, Tizian Schneider, Tobias Baur, Caroline Schultealbert
Publikováno v:
I2MTC
This paper shows the opportunities of data preprocessing and how it influences the time required to record a sufficient amount of valid calibration data samples. Specifically, we approach the minimum needed time for calibration from two sides: on the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4c2223c96503f7354d865bf099f0aae1
https://doi.org/10.1109/i2mtc50364.2021.9459919
https://doi.org/10.1109/i2mtc50364.2021.9459919
Publikováno v:
Applied Sciences
Volume 11
Issue 5
Applied Sciences, Vol 11, Iss 2199, p 2199 (2021)
Volume 11
Issue 5
Applied Sciences, Vol 11, Iss 2199, p 2199 (2021)
Trust in artificial intelligence (AI) predictions is a crucial point for a widespread acceptance of new technologies, especially in sensitive areas like autonomous driving. The need for tools explaining AI for deep learning of images is thus eminent.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4d22544e53b4f7bb5770f4ad28b0341a
Autor:
Anna Wedell, Malcolm G. MacKenzie, Siavash Ghaderi-Sohi, Ariana Kariminejad, Rolph Pfundt, Magnus Nordenskjöld, Maartje van de Vorst, Peter Conner, Anna Wredenberg, Marloes Steehouwer, Alexander Hoischen, Nursel Elcioglu, Hülya Kayserili, Hamidreza Setayesh, Denny Schanze, Birgit Krabichler, Cynthia J. Curry, Gabriele Gillessen-Kaesbach, Christoph Freyer, Kym M. Boycott, Ann Nordgren, Christian Gilissen, Andreas R. Janecke, Giedre Grigelioniene, Mohamad Hasan Kariminejad, Rocio Acuna-Hidalgo, Dagmar Wieczorek, Daniel Nilsson, Martin Zenker, Payman Goodarzi
Publikováno v:
American Journal of Human Genetics, 95, 285-293
American Journal of Human Genetics, 95, 3, pp. 285-293
American Journal of Human Genetics, 95, 3, pp. 285-293
Contains fulltext : 136372.pdf (Publisher’s version ) (Closed access) Neu-Laxova syndrome (NLS) is a rare autosomal-recessive disorder characterized by a recognizable pattern of severe malformations leading to prenatal or early postnatal lethality.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::91ce6c5fac299a81c11c35eef6832bcd
https://pubmed.ncbi.nlm.nih.gov/25152457
https://pubmed.ncbi.nlm.nih.gov/25152457
Publikováno v:
2011 International Symposium on Integrated Circuits.
In this paper a second-Order low distortion Sigma-Delta Modulator (SDM) with utilization of comparator-based switched-capacitor (CBSC)-based IIR filter, is explored. The advantages of this new structure are justified by the reductions of power and ar
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7f121f83aab19aac05e6bf96fe0a2833
https://doi.org/10.1109/isicir.2011.6131993
https://doi.org/10.1109/isicir.2011.6131993