Zobrazeno 1 - 10
of 40
pro vyhledávání: '"Hongyan Mei"'
Publikováno v:
Applied Sciences, Vol 13, Iss 22, p 12392 (2023)
Temporal knowledge graph completion (TKGC) refers to the prediction and filling in of missing facts on time series, which is essential for many downstream applications. However, many existing TKGC methods suffer from two limitations: (1) they only co
Externí odkaz:
https://doaj.org/article/52e05970bd794965be9fe847dda27aaa
Publikováno v:
Applied Sciences, Vol 13, Iss 18, p 10524 (2023)
Due to the fast retrieval speed and low storage cost, cross-modal hashing has become the primary method for cross-modal retrieval. Since the emergence of deep cross-modal hashing methods, cross-modal retrieval significantly improved. However, the exi
Externí odkaz:
https://doaj.org/article/7c36afb7a5b343bfb6bd0be29a8a84f6
Autor:
Alexander Koch, Hongyan Mei, Jura Rensberg, Martin Hafermann, Jad Salman, Chenghao Wan, Raymond Wambold, Daniel Blaschke, Heidemarie Schmidt, Jürgen Salfeld, Sebastian Geburt, Mikhail A. Kats, Carsten Ronning
Publikováno v:
Advanced Photonics Research, Vol 4, Iss 2, Pp n/a-n/a (2023)
Heavy and hyper doping of ZnO by a combination of gallium (Ga) ion implantation using a focused ion beam (FIB) system and post‐implantation laser annealing is demonstrated. Ion implantation allows for the incorporation of impurities with nearly arb
Externí odkaz:
https://doaj.org/article/e46dab54b73f4096a459f0aa4d857fa2
Publikováno v:
Applied Sciences, Vol 13, Iss 3, p 1786 (2023)
This paper proposes a novel graph neural network recommendation method to alleviate the user cold-start problem caused by too few relevant items in personalized recommendation collaborative filtering. A deep feedforward neural network is constructed
Externí odkaz:
https://doaj.org/article/b3ba3db31fb3410480abb886a9043eac
Publikováno v:
Applied Sciences, Vol 12, Iss 19, p 9861 (2022)
The encoder–decoder framework is the main frame of image captioning. The convolutional neural network (CNN) is usually used to extract grid-level features of the image, and the graph convolutional neural network (GCN) is used to extract the image
Externí odkaz:
https://doaj.org/article/5e61463febc34aff8933ca3e79a465f7
Publikováno v:
The Journal of Engineering (2019)
Ground-based synthetic aperture radar (GB-SAR) is a novel system applied deformation monitoring of buildings, mountains, and mining slopes with the advantages of high-resolution, large-scale monitoring, and fast image acquisition image interval. Most
Externí odkaz:
https://doaj.org/article/d2e442c52a06441db91a6f0e70b08f55
Publikováno v:
The Journal of Engineering (2019)
Multiple-input multiple-output (MIMO) imaging radar is a new kind of new imaging radar in recent years. It can achieve faster data acquisition speed than the traditional ground-based SAR due to the ability to get a large number of multi-channel data
Externí odkaz:
https://doaj.org/article/08107967d00044679cbcf25791781530
Publikováno v:
The Journal of Engineering (2019)
Multiple-input multiple-output (MIMO) radar plays a more and more important role in radar imaging, target detection, and other fields owing to its unique array structure. Transmitting orthogonal signals by different transmitters, a MIMO radar can sig
Externí odkaz:
https://doaj.org/article/49e2c7a31b054c67a2ec749ff658b51f
Publikováno v:
In Procedia Computer Science 2018 131:706-716
Autor:
Samir Rosas, Keegan A. Schoeller, Edward Chang, Hongyan Mei, Mikhail A. Kats, Kevin W. Eliceiri, Xinyu Zhao, Filiz Yesilkoy
Publikováno v:
Advanced Materials.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7e778e37ce64c9413ac0f3e01db93b0b
https://doi.org/10.1002/adma.202301208
https://doi.org/10.1002/adma.202301208