Zobrazeno 1 - 10
of 307
pro vyhledávání: '"02"'
Publikováno v:
Artificial Life and Robotics. 26(3):354-359
Depth estimation is one of the basic and important tasks in 3D vision. Recently, many works have been done in self-supervised depth estimation based on geometric consistency between frames. However, these research works still have difficulties in ill
Publikováno v:
SN Applied Sciences, Vol 3, Iss 6, Pp 1-17 (2021)
With aim of detecting breast cancer at the early stages using mammograms, this study presents the formulation of five feature types by extending the information set to encompass the concept of an intuitionist fuzzy set. The resulting pervasive inform
Publikováno v:
SN Applied Sciences, Vol 3, Iss 6, Pp 1-10 (2021)
Significant advances in deep learning techniques have made it possible to offer technologically advanced methods to detect cardiac abnormalities. In this study, we have proposed a new deep learning based Restricted Boltzmann machine (RBM) model for t
Autor:
Amarsagar Reddy Ramapuram Matavalam, Decebal Constantin Mocanu, Shiwei Liu, Yulong Pei, Mykola Pechenizkiy
Publikováno v:
Neural Computing and Applications, 33(7), 2589-2604. Springer
Artificial Neural Networks (ANNs) have emerged as hot topics in the research community. Despite the success of ANNs, it is challenging to train and deploy modern ANNs on commodity hardware due to the ever-increasing model size and the unprecedented g
Publikováno v:
Artificial Life and Robotics. 26(1):149-154
This paper proposes a security testbed system for industrial control systems. In control systems, controllers are final fortresses to continue the operation of field systems. Then, we need countermeasures of controllers. The whitelisting function is
Autor:
Christos Anagnostopoulos, Madalena Soula, Kostas Kolomvatsos, George Stamoulis, Anna Karanika
Current advances in the Internet of Things (IoT) and Cloud involve the presence of an additional layer between them acting as mediator for data transfer and processing in close distance to end users. This mediator is the edge computing (EC) infrastru
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4f2af5549b397cdb92123d2cd3e997a6
https://eprints.gla.ac.uk/238281/2/238281.pdf
https://eprints.gla.ac.uk/238281/2/238281.pdf
Autor:
Masaya Sato, Toshihiro Yamauchi, Kritsana Chaikaew, Hiroyuki Uekawa, Yuta Imamura, Rintaro Orito, Pattara Leelaprute
Publikováno v:
International Journal of Information Security. 20:833-847
Many Android apps employ WebView, a component that enables the display of web content in the apps without redirecting users to web browser apps. However, WebView might also be used for cyberattacks. Moreover, to the best of our knowledge, although so
Autor:
Shin-ei Kudo, Yukitaka Nimura, Yutaka Saito, Kensaku Mori, Hiroaki Ikematsu, Masahiro Oda, Yuichiro Hayashi, Hayato Itoh, Yuichi Mori, Masashi Misawa, Shoichi Saito, Kazuo Ohtsuka, Kinichi Hotta
Publikováno v:
International Journal of Computer Assisted Radiology and Surgery. 15(12):2049-2059
Purpose: An endocytoscope is a new type of endoscope that enables users to perform conventional endoscopic observation and ultramagnified observation at the cell level. Although endocytoscopy is expected to improve the cost-effectiveness of colonosco
Autor:
Jonathan Readshaw, Stefano Giani
Publikováno v:
Neural Computing and Applications, 2021, Vol.33(24), pp.17353-17367 [Peer Reviewed Journal]
This work presents a convolutional neural network for the prediction of next-day stock fluctuations using company-specific news headlines. Experiments to evaluate model performance using various configurations of word embeddings and convolutional fil
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::246f068e4e1f804c398ed85921b63aad
http://dro.dur.ac.uk/33342/1/33342.pdf
http://dro.dur.ac.uk/33342/1/33342.pdf
Publikováno v:
Medical & Biological Engineering & Computing. 58(6):1239-1250
High-quality annotations for medical images are always costly and scarce. Many applications of deep learning in the field of medical image analysis face the problem of insufficient annotated data. In this paper, we present a semi-supervised learning