Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Mattern, Denny"'
The design of quantum circuits is often still done manually, for instance by following certain patterns or rule of thumb. While this approach may work well for some problems, it can be a tedious task and present quite the challenge in other situation
Externí odkaz:
http://arxiv.org/abs/2302.01303
Autor:
Wörmann, Julian, Bogdoll, Daniel, Brunner, Christian, Bührle, Etienne, Chen, Han, Chuo, Evaristus Fuh, Cvejoski, Kostadin, van Elst, Ludger, Gottschall, Philip, Griesche, Stefan, Hellert, Christian, Hesels, Christian, Houben, Sebastian, Joseph, Tim, Keil, Niklas, Kelsch, Johann, Keser, Mert, Königshof, Hendrik, Kraft, Erwin, Kreuser, Leonie, Krone, Kevin, Latka, Tobias, Mattern, Denny, Matthes, Stefan, Motzkus, Franz, Munir, Mohsin, Nekolla, Moritz, Paschke, Adrian, von Pilchau, Stefan Pilar, Pintz, Maximilian Alexander, Qiu, Tianming, Qureishi, Faraz, Rizvi, Syed Tahseen Raza, Reichardt, Jörg, von Rueden, Laura, Sagel, Alexander, Sasdelli, Diogo, Scholl, Tobias, Schunk, Gerhard, Schwalbe, Gesina, Shen, Hao, Shoeb, Youssef, Stapelbroek, Hendrik, Stehr, Vera, Srinivas, Gurucharan, Tran, Anh Tuan, Vivekanandan, Abhishek, Wang, Ya, Wasserrab, Florian, Werner, Tino, Wirth, Christian, Zwicklbauer, Stefan
The availability of representative datasets is an essential prerequisite for many successful artificial intelligence and machine learning models. However, in real life applications these models often encounter scenarios that are inadequately represen
Externí odkaz:
http://arxiv.org/abs/2205.04712
Image classification is an important task in various machine learning applications. In recent years, a number of classification methods based on quantum machine learning and different quantum image encoding techniques have been proposed. In this pape
Externí odkaz:
http://arxiv.org/abs/2106.07327
Publikováno v:
International Journal of Data Science & Analytics; May2024, Vol. 17 Issue 4, p337-357, 21p
Akademický článek
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Autor:
Cavojska, Jana, Petrasch, Julian, Mattern, Denny, Lehmann, Nicolas J., Voisard, Agnès, Böttcher, Peter
Computing 3D bone models using traditional Computed Tomography (CT) requires a high-radiation dose, cost and time. We present a fully automated, domain-agnostic method for estimating the 3D structure of a bone from a pair of 2D X-ray images. Our trip
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______610::b55f746c8cbe9184ecb03a27ec1b4de2
https://publica.fraunhofer.de/handle/publica/263201
https://publica.fraunhofer.de/handle/publica/263201
Akademický článek
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Autor:
Čavojská, Jana, Petrasch, Julian, Mattern, Denny, Lehmann, Nicolas Jens, Voisard, Agnès, Böttcher, Peter
Publikováno v:
Communications Biology
Communications Biology, Vol 3, Iss 1, Pp 1-13 (2020)
Communications Biology, Vol 3, Iss 1, Pp 1-13 (2020)
Computing 3D bone models using traditional Computed Tomography (CT) requires a high-radiation dose, cost and time. We present a fully automated, domain-agnostic method for estimating the 3D structure of a bone from a pair of 2D X-ray images. Our trip