Zobrazeno 1 - 10
of 213
pro vyhledávání: '"Justin Zhan"'
Autor:
Matthew Swan, Justin Zhan
Publikováno v:
IEEE Access, Vol 9, Pp 72377-72386 (2021)
A hypergraph is a generalization of a graph in that the restriction of pairwise affinity scores is lifted in favor of affinity scores that can be evaluated between an arbitrary number of inputs. Hypergraphs clustering is the process of finding groups
Externí odkaz:
https://doaj.org/article/eee6eabe1ad8456b85c95363715e0048
Publikováno v:
IEEE Access, Vol 8, Pp 82201-82214 (2020)
Many arrhythmia datasets are multimodal due to the simultaneous collection of physiological signals of a subject. These datasets frequently have missing modalities or missing block-wise data, a characteristic that various recent applications of neura
Externí odkaz:
https://doaj.org/article/fbf6a7879c8e457e919cb05dd12e1a58
Autor:
Zhiwei Fang, Justin Zhan
Publikováno v:
IEEE Access, Vol 8, Pp 24506-24513 (2020)
In this paper, we propose a physical informed neural network approach for designing the electromagnetic metamaterial. The approach can be used to deal with various practical problems such as cloaking, rotators, concentrators, etc. The advantage of th
Externí odkaz:
https://doaj.org/article/7f393458fa884a96bc4286902bdd68f1
Publikováno v:
IEEE Access, Vol 8, Pp 26433-26444 (2020)
This paper proposes a number of theorems and algorithms for the Chinese Remainder Theorem, which is used to solve a system of linear congruences, and the extended Rabin cryptosystem, which accepts a key composed of an arbitrary finite number of disti
Externí odkaz:
https://doaj.org/article/d18452fec76c4cb98dca6b38b960489d
Autor:
Zhiwei Fang, Justin Zhan
Publikováno v:
IEEE Access, Vol 8, Pp 26328-26335 (2020)
Partial differential equations (PDEs) on surfaces are ubiquitous in all the nature science. Many traditional mathematical methods has been developed to solve surfaces PDEs. However, almost all of these methods have obvious drawbacks and complicate in
Externí odkaz:
https://doaj.org/article/bbaec595404c45acbc89f89ca46d6b15
Publikováno v:
Frontiers in Artificial Intelligence, Vol 4 (2021)
Deep learning models have been shown to be effective for material analysis, a subfield of computer vision, on natural images. In medicine, deep learning systems have been shown to more accurately analyze radiography images than algorithmic approaches
Externí odkaz:
https://doaj.org/article/3d8f6a57642a4db2a26bed8ba4a284b3
Autor:
Sanket Chobe, Justin Zhan
Publikováno v:
Journal of Big Data, Vol 6, Iss 1, Pp 1-33 (2019)
Abstract As social network structures evolve constantly, it is necessary to design an efficient mechanism to track the influential nodes and accurate communities in the networks. The attributed graph represents the information about properties of the
Externí odkaz:
https://doaj.org/article/bcdf4307d38742a9bb30628498bbb257
Autor:
Andrea Hart, Brianna Smith, Sean Smith, Elijah Sales, Jacqueline Hernandez-Camargo, Yarlin Mayor Garcia, Felix Zhan, Lori Griswold, Brian Dunkelberger, Michael R. Schwob, Sharang Chaudhry, Justin Zhan, Laxmi Gewali, Paul Oh
Publikováno v:
Journal of Big Data, Vol 6, Iss 1, Pp 1-12 (2019)
Abstract The human brain is a complex system of neural tissue that varies significantly between individuals. Although the technology that delineates these neural pathways does not currently exist, medical imaging modalities, such as diffusion magneti
Externí odkaz:
https://doaj.org/article/6c88ca26a4434fb7b7049c430974103e
Autor:
Binay Dahal, Justin Zhan
Publikováno v:
IEEE Access, Vol 7, Pp 141171-141178 (2019)
Image Aesthetics Analysis is a challenging research problem as aesthetics of an image is a subjective quality and it is quite difficult to formulate it into a mathematical or algorithmic problem. On the other hand, its applications are numerous, rang
Externí odkaz:
https://doaj.org/article/b9a8a10ef8914febb08beaa0dbb2dae9
Autor:
Carter Chiu, Justin Zhan
Publikováno v:
IEEE Access, Vol 7, Pp 178331-178341 (2019)
Neural networks are the cutting edge of artificial intelligence, demonstrated to reliably outperform other techniques in machine learning. Within the domain of neural networks, many different classes of architectures have been developed for various t
Externí odkaz:
https://doaj.org/article/04d03b75cf804d388bbe6f8c5ec317a5